For the past several years, intra-logistics activity has been highly impacted by a drastic change in the behavior of consumer society and by the development of novel technologies. The constant increase in demand is forcing the main players in logistics to become increasingly responsive and competitive. It has become vital to improve and optimize routing, storage and customer-order picking solutions. The firm SAVOYE, a builder of customer-order-picking equipment, is specialized in the automation and computerization of logistical warehouses and is constantly improving and evaluating its solutions.
The management of a logistical warehouse includes the procurement of supplies, the receiving and management of flows and stocks. Improving travel time for a customer order often means minimizing its conveyance time. 50% of the picking time (preparation time) for a customer order is devoted to this conveying operation, according to De Koster, R., Le-Duc, T., and Roodbergen, K. J., “Design and control of warehouse order picking: a literature review” (2007), European Journal of Operational Research 182(2), 481-501. It is therefore necessary first of all to look at the main problem faced by warehouses, that of optimizing the flows conveyed in order to ensure the highest possible production rate. We shall focus more particularly on the intersections of flows of loads (packages, bins, containers, etc.). The goal is to maximize the throughput of the final flow (also called an outgoing flow or outflow) combining various incoming flows (inflows) coming from different places.
In a logistical warehouse, it happens that several incoming flows of loads (also called injection flows) are grouped together into a single outgoing flow (or outflow) (also called an exit flow). A flow of loads corresponds to a list of sequenced loads, filing past one after the other. These flows can be transported by a conveyor that is similar to a conveyor belt moving all the loads situated on it in a given sense in single file. Here below in the description, conveyors that transport incoming flows are called lanes and the conveyor transporting the exit flow is called a collector.
The injection flows are distributed all along the collector. The positions of the loads composing these injection flows are known and identifiable. For each injection flow, we can choose the instant at which its first load is injected into the collector. A sequential distribution of the injection flows enables a lane situated upstream to the flow of the collector to benefit from a number of injection possibilities greater than that of a lane situated downstream. Indeed, the latter can shed its loads only when there is space left free by the lanes further upstream.
In order to prevent an imbalance of injection of loads between the incoming flows, it is preferred to make a definition in advance of the order of the loads once they are all placed on the collector (this order is called a final sequence or, again, an exit sequence).
The governing idea of the present disclosure is to push the flow of the collector to the maximum mechanical capacity of the collector. To this end, the number of vacant spaces in the collector needs to be limited. We propose an approach based on the right dates for injecting loads, to constitute a final flow that has no vacant spaces (or as few of them as possible). These injection dates are defined in order to comply with every achievable final sequence, namely every sequence complying with FIFO (First-in-first-out) sequential orders of the injection flows.
The solution proposed and described here below to respond to this set of problems and issues is novel and inventive with respect to known models of scheduling problems, described for example in:
In short, the system studied is composed of injection flows (incoming flows) transported by lanes (set of conveyors) and a collector (another conveyor) combining these injection flows into a single final flow (outgoing flow). The control system (or overall control system) proposed and described here below can be applied especially but not exclusively to a “continuous non-accumulation conveyor” type of collector or a sorter type collector (belt tray, tilt tray, etc.). This control system enables compliance with any final achievable sequence whatsoever. We therefore give the solution corresponding to the optimal throughput relative to a final given sequence. If no final sequence is desired, we are capable of obtaining the maximum throughput on a completely unoccupied collector in order to combine these injection flows.
However, in certain cases, obstructions can already occupy places on the collector. The term “obstruction of a time step (or time span”) of the collector” is understood to mean especially but not exclusively a disturbing load coming from a disturbing flow different from the injection flows. An obstruction is not necessarily a disturbing load but can also be a place of the collector that is damaged, reserved, etc. In this case, the management of the injection flows must take such obstructions into account.
In the particular case where the disturbing loads come from one or more disturbing flows, we can distinguish two types of disturbing flows. A disturbing flow is said to be “non-controlled” if the injection into the collector of the disturbing loads that compose it cannot be controlled by the control system (these disturbing loads arrive without taking account of the environment). By opposition, a disturbing flow is said to be “controlled” if the injection on the collector of the disturbing loads composing it can be controlled by the control system. Our proposed control system supports these different types of disturbing flows (non-controlled or controlled) and gives an optimal solution including the management of the disturbing flows to be controlled.
One illustratory and non-exhaustive example of a concrete application is that of the GTP Intelis PTS (Goods To Person Intelis Picking Tray System) proposed by the firm SAVOYE. This is a comprehensive automated customer-order picking solution in which an automated shuttle-based storage and retrieval (or removal) system (called the Intelis PTS system) 3 enables the feeding of picking stations (also called GTP stations) 4 at very high speeds. The role of the automated system (Intelis PTS) is therefore to store and obtain the entry and the exit of the loads comprising articles needed for the efficient filling of the customer orders at the GTP stations. The automated system consists of several storage racks (also called PTS aisles which however should not be mistaken for lanes (in the sense of conveyors) transporting incoming flows in the context of the present invention (see explanations here below), each composed of shuttles and elevators enabling the to-and-fro movement of these loads respectively on the entry conveyors 51, 52 and exit conveyors 21, 22. These different entry and exit conveyors are all connected by a collector 1 which feeds the picking stations 4 as can be seen in
To establish a link with the contextual definition here above, the exit conveyors 21, 22 of the automated system 3 form the conveyors (also called “lanes”) transporting the incoming payload flows, these incoming flows being merged on the collector 1 into an outgoing flow of payloads.
In other words, the to-and-fro movement of the loads that enter and exit the automated system 3 is managed by means of the collector. We therefore have several injection flows of loads (also called incoming flows in the present discussion of problems and issues) on the exit conveyors 21, 22 of the automated system 3, all injected on the collector.
In addition, when the flows of loads that return to the automated system 3 (via the entry conveyor 51, 52) pass through the same collector 1, we have an example of disturbing flows, called return flows in this particular case. These disturbing flows are highly interesting because they disappear after the passage of all the injection zones, thus creating vacant spaces for certain injection flows but not for others. As described in detail here below, one embodiment of the proposed solution is aimed at controlling, as far as is possible, these disturbing flows to fill these vacant spaces rather than to let them exist.
The solutions proposed in this example of an application are described here below in the document.
In a first particular embodiment of the invention, a method is proposed for merging, within a logistical warehouse, k incoming flows of payloads, transported respectively by k conveyors called lanes ai with i∈{1, . . . , k}, into one outgoing flow of payloads transported by another conveyor called a collector, the logistical warehouse being such that:
According to one particular characteristic of the first embodiment, Δi,i′ is a time-related distance between the lanes ai and ai′ expressed in time units, each corresponding to a time span of the collector and the method furthermore comprises the following steps:
In a second particular embodiment of the invention, a method is proposed for merging, within a logistical warehouse, k incoming flows of payloads, transported respectively by k conveyors called lanes ai with i∈{1, . . . , k}, into one outgoing flow of payloads, transported by another conveyor called a collector, the logistical warehouse being such that:
According to one particular characteristic of the second embodiment, the step of commanding the collector and the k lanes for an injection of the n payloads into the collector in compliance with the n injection dates T(u),∀u∈L, is preceded by the following steps:
According to one particular characteristic of the second embodiment, Δi,i, is a time-related distance between the lanes ai and ai′ expressed in time units each corresponding to a time span of the collector and the method furthermore comprises the following steps:
According to one particular characteristic of the first or second embodiment of the invention, the date t0 is computed with the following formula:
According to one particular characteristic of the first or second embodiment, the method is executed iteratively, each new execution being carried out at a new instant Tb computed with the following formula:Tb=(ulast)+Δ1+Δi
According to one particular characteristic of the first or second embodiment, the method is executed iteratively, each new execution being carried out at a new instant Tb defined as an instant at which no load of the exit sequence σ of a preceding execution at a preceding instant Tb is situated in a portion of the collector extending from the first lane a1 to the lane ai
According to one particular characteristic of the first or second embodiment, the method is executed iteratively, each new execution being carried out at a new instant Tb computed with the following formula: Tb=Max(Tb+1, T(ulast)−Δ1+Δi
Another embodiment of the invention proposes a computer program product comprising program code instructions for the implementing of the above-described method (in any one of its different embodiments), when said program is executed on a computer.
Another embodiment of the invention proposes a computer-readable and non-transient storage medium storing a computer program comprising a set of instructions executable by computer to implement the above-mentioned method (in any one of its different embodiments).
Another embodiment of the invention proposes a control system (device) comprising means for implementing steps that it performs in the method as described here above in any one of its different embodiments.
In the following description, given by way of an indicative and non-exhaustive example, reference is made to the appended drawings, of which:
As mentioned further above, the system under study is formed by a drain-off system (a conveyor called a collector), several other conveyors (called lanes) and loads. The system is dynamic, and the loads are transported by the lanes, injected into the collector and then transported by the collector. In a first stage, we shall consider the state of this system in freezing the position of each load present in it at a given instant. We shall define the frozen sub-systems of this system to be able to compute future dates of injection of certain loads. This corresponds to the resolution of the static problem. Section 7 shall examine the way to control and steer this system dynamically.
The table here below is a summary of the notations.
For a configuration of the system at a given instant, each lane will comprise an ordered set of loads. Let k be the number of lanes in our system, each lane being numbered a1 to ak in the sense of movement of the collector. These lanes respectively possess a number hi of loads represented by a First-In-First-Out (FIFO) list that has to be injected one by one into the collector.
An example is given in
There are n loads (boxes, bins, containers, etc.) in all to be injected into the collector, coming from the different injection flows. Let L denote the set of these loads and u=ai(j) a load u belonging to L, coming from the jth position in the lane ai.
In addition, let σ be the exit sequence in which these loads must be ordered once they are all injected into the collector. The function ø(u) gives the position of the load u in this sequence. Each load can thus be identified by a single “sequence” number between 1 and n, corresponding to its position in the desired exit sequence (σ). This is how we will identify the loads here below. It can be noted that, in this case, it is easy to verify if the sequence is achievable: it is enough for each lane to have an ordered list of loads identified by sequence numbers in rising order that are not necessarily consecutive.
Let us now specify the set L′, specially grouping together the first loads awaited in the final exit sequence, placed at the first position of the lanes a1, a2, . . . , ai
It may be recalled that each lane corresponds to an injection flow at a given instant, represented as a FIFO column attached to the collector. However, in the warehouse, it can happen that the load awaiting injection is at a distance from the collector. Let departure point denote the place at which this load awaits the order to depart from its lane (conveyor), illustrated by a point attached to the FIFO column, and let injection point denote the space of the collector that is the first to be touched by the load in the course of being really injected into this collector, illustrated by a dot attached to the collector in
In the diagrams of the system in lanes, these two points (dots) coincide and are represented in black in
The drain-off system (or collector) will be considered as a system with time spans (like a sorter) also called slots or positions.
Thus, our goal of obtaining a maximum throughput with an ordered outgoing flow amounts to filling the spans of the collector as can be seen in
We shall consider a time unit corresponding to this time span that sub-divides the collector, according to its speed of movement. A time unit, called a “time span”, corresponds to the duration needed for a point of the collector to move exactly by the physical distance corresponding to one position. The distance defined for this position corresponds to the size of a load plus a security distance. This security distance must be adjusted according to the needs of those skilled in the art and in order to comply with the following condition (illustrated in
The time unit must obligatorily be greater than the time taken by a load to be injected into the collector from the time when a part of the load touches the collector up to the time when the entire load is placed accurately on the collector (i.e. in its flow).
5.2.2 Distance from the Injection System
As illustrated in
The time distance between two lanes ai and aj is denoted as Δi,j, the second index being the lane relative to which operation is situated.
The following table is a summary of the notations of the Job Shop model
For each exit sequence σ, we model the system as a unit-job Job Shop model, with n jobs and k machines. Each load of the sequence σu (uth load of this sequence) is associated with a job Ju and each lane ai is associated with a machine Mi. Each job Ju associated with a load contained in the lane ai must follow an ordered list of k−i+1 unit operations {ou,i, ou,{i+1}, . . . , ou,k}. An operation denoted as ou,i is a unit job of the job Ju to be performed specifically on the machine Mi. A job can be assigned to only one machine at a time and a machine can carry out only one operation at a time.
We shall try to schedule these jobs on the machines in complying with the sequential order given by their respective list of operations. The goal is to schedule them in order to minimize the total duration of execution of all these jobs.
In this part, we shall consider a collector processing only the injection flows. The collector is entirely vacant and ready to retrieve the injection flows. Only the merger of these injection flows must be controlled to accurately inject their loads in order to have a final flow that is fluid, continuous and corresponds to the desired exit sequence.
In order to simplify matters, we shall assume that the injection flows are distributed consecutively on the collector in such a way that a time interval is needed for a load on the collector to pass from one injection zone to the next as can be seen in
We shall explain the modelling of the system as a problem of Job Shop scheduling in this particular case.
Each of then loads is associated with a job Ju, u∈{1, . . . , n}, with numbering in accordance with the sequence number of the load. Thus, if σu corresponds to the uth load in the sequence σ, then its associated job is Ju. The operations of these jobs must be processed by a set of k machines {M1, . . . , Mk}. An operation can be allotted to only one machine at a time. Each machine is associated with a lane (i.e. an injection flow) that can carry out only one operation at a time. It may be recalled that these lanes are numbered {a1, . . . , ak}, from upstream to downstream (i.e. according to the sense of conveyance of the collector).
Thus, a load σu being injected into the collector from the lane ai will pass in front of each lane aj with j in {i, i+1, . . . , k}. This mechanism is represented by the fact that each job associated with a load of the lane ai is composed of k−i+1 unit operations {ou,i, ou,{i+1}, . . . , ou,k} to be processed consecutively without waiting. Each operation has to be scheduled on a specific machine. Thus, if the operation ou,i (processed by the machine Mi) starts at the instant t, the operation ou,{i+1} (processed by the machine M{i+1}) starts at the instant t+1, etc., and finally the operation ou,k (processed by the machine Mk) starts at the instant t+k−i.
If the starting instant of the first operation ou,i of this job corresponds to the date of injection into the collector, the starting instants of the following operations (c.-à-d. {ou{i+1}, . . . , ou,k}) represent the instants at which the load is in front of the following lanes.
It can be noted that each job is composed of at least one operation on the last machine Mk (since each load passes in front of at least the last lane ak). The sequence of the operations scheduled on the machine Mk corresponds exactly to the order in which the loads will pass in front of the last lane and their departure date corresponds to the instant when these loads will pass in front of this last injection lane. This is why, if the load u is before the load v in the given exit sequence, the last operation of u must begin before the last operation of v on Mk.
The goal of not having space on the collector amounts to not having idle time between the operations of the machine Mk.
The scheduling problem proposed here above can be resolved by the following algorithm.
The real dates of injection into the collector are deduced directly from the start of the first operation of each job. The time unit used is the one defined here above (“the time span” of the collector).
Now that we have described how the algorithm for resolving the scheduling problem works, we shall deduce the formula used to compute the injection dates.
The notations used in the formula here below are those of the summary table discussed further above.
Let us fix the origin of the time at the earliest date of injection of the very first load or loads injected into the collector. In the present system, the unoccupied location that will receive this load is therefore placed just in front of the lane of this load at the instant 0. Thus, we will compute the date
corresponding to the earliest date at which the first load of the sequence passes in front of the lane ak.
Proof: Let 0 be the date at which the injection of the load starts. Let t0 be the date at which the first load of the sequence (i.e. σ1) passes in front of the lane ak. We note that the first load injected into the collector is necessarily a load at the head of a lane, in a lane situated from the lane a1 to the lane of σ1. Let L′⊂L be this sub-set of loads.
Therefore, for any load u=ai(j)∈L′, we know that if it were to be injected at the date x, it would pass in front of the lane ak at the date x+k−i. We have x≥0 since we cannot inject the load before the date 0. Now, by definition of t0, the load u will pass in front of the lane ak at the date t0+σ(u)−1=x+k−i. That is, t0+σ(u)−1−k+i=x≥0.
From this, we deduce that for all u=ai(j)∈L′, t0≥k+1−i−σ(u). We search for the earliest date enabling the verification of all these constraints, therefore:
The algorithm 1 here below gives the dates of injection T(u), i.e. the dates of entry of each load u into the collector. The time unit used is the “time span” defined further above. The algorithm 1 gives the formula for computing these injection dates should the flows get injected at each consecutive location on the collector (see
In scheduling, the Gantt chart is a very useful tool for viewing, in time, the operations composing a job. This tool will enable us to graphically represent the progress of the work of each machine and visually show us the solution provided to our problem. In addition, we can see the link between the results obtained by the algorithm enabling the injection dates to be attained and the associated formula.
Let us take the configuration of the system as follows (see
In this simplified case, we can represent the Job Shop solution in a Gantt chart such that each row corresponds to one machine. The fact that each load passes by the machines consecutively is represented by the fact that each load sequence number appears in consecutive boxes from left to right in the table (see
We find the desired sequence, without vacant space, on the machine M4 and the date of injection of each load is given by the reading of the box of the first appearance (from left to right) of the sequence number giving the identification of this load.
6.2 Solution for Lanes with any Unspecified Distribution
Now that the simplified case has been seen, let us consider the general case of the collector that processes only the injection flows. The flows therefore no longer get injected consecutively at each time span of the collector but are distributed in any unspecified way. The distances between lanes are known. It is the travel time between the point of injection of the lane ai and the last lane ak that is of particular interest to us. It will be denoted Δi=Δi,k (as defined further above).
The algorithm 2 here below takes account of this notion of any unspecified time distance between lanes and thus responds to the general case of the collector dedicated to injection flows.
Let us again consider the date 0 as being the date of the first possible injection. This time, a load u of the lane i injected at the date x arrives in front of the lane ak at the date x+Δi. Thus, we obtain the earliest date at which the first load of the sequence passes in front of the lane ak by the formula
Let us take an example similar to that of paragraph 6.1.4 in setting aside the lanes this time.
Let us take the configuration of the system as follows (see
which we find actually by definition at the instant 11 on the graph.
Here, for ease of comprehension, we give an example with inter-lane distances that are integer values but it is possible to take non-integer values in numbers of “time spans”.
Each injection flow (incoming flow) is represented by a lane containing a list of loads in a FIFO order. The number of lanes can vary from 2 to k, and the list of the lane i contains hi loads (hi can be zero). There are, in all, n loads to be merged into collector. Let us take for example (see
In addition, staying with the general case, we shall take the resolutions of this general case with Δ1=1 and Δ2=0.
When the final sequence of the loads on the collector is of no importance, it is enough to define, in any unspecified way an achievable sequence that sets the order of the loads.
We can design different ways of defining a “default” exit sequence:
This sequence σ′ can be seen as a given exit sequence for the algorithm which computes the injection dates. This sequence is obligatorily achievable and minimizes the disorder. We obtain a maximum throughput with a minimum disorder for the outgoing flow from the collector.
Since it is always possible to assign a single sequence number from 1 to n to all the loads, corresponding to their position in the final sequence σ, we shall display the loads with these sequence numbers to identify them and characterize them entirely (cf.
Let us keep this configuration to continue the study of the example.
In the present example, L′ brings together the loads numbered 1 and 5.
We search for the maximum between {Δ2+1−σ(1), Δ1+1−σ(5)}, and we obtain t0=0.
T(1)=t0+σ(1)−1−Δ2=0
T(2)=t0+σ(2)−1−Δ2=1
T(3)=t0+σ(3)−1−Δ2=2
T(4)=t0+σ(4)−1−Δ2=3
T(5)=t0+σ(5)−1−Δ1=3
T(6)=t0+σ(6)−1−Δ1=4
T(7)=t0+σ(7)−1−Δ1=5
T(8)=t0+σ(8)−1−Δ1=6
T(9)=t0+σ(9)−1−Δ1=7
T(10)=t0+σ(10)−1−Δ2=9
The dates of injection T(u) being given in the time unit (i.e. the time span of the collector), this amounts visually to seeing the collector move by one span at each time unit. If we view an image of the system at each time unit, each load u appears for the first time on the collector at the date T(u) (its injection date).
The configuration of the collector at the instant 0 (cf.
The load 2 must be injected at the instant 1, which means that it is on the collector after the movement by one step of the collector, as is shown by
The load 3 is injected at the instant 2, as is shown by
The loads 4 and 5 are injected at the date 3, as is shown by
And so on and so forth.
The computation of the injection dates is done on a given state of the system. With the system developing in time, a first possibility consists in redoing this computation whenever a new load arrives at the system because it has does not yet have its definite injection date. However, instead of also regularly launching the computation algorithm, which is not advantageous for various reasons (in particular the consumption of computation resources), it is preferable to proceed by batches. This kind of batchwise operation is explained in this section.
We would like a flow (outgoing flow) that is continuous and optimal on the collector throughout a workday. We have just seen how to define an optimal injection date (in order to arrive at our goal) on the loads present in the lanes at a given fixed instant. This goal now needs to be attained for all the loads arriving by the injection flows at any given instant. We propose to call the injection date computation algorithm at the instant needed to obtain a fluid and continuous filling of the collector. To this end, in this section, we define the way to fill the FIFO lists of each lane for the configuration of the system at a fixed instant. Then, we define what a batch is and then finally explain this succession of the processing of two batches without leaving any vacant space on the collector.
In each lane, there is a list of loads with a unique sequence number for each load. These sequence numbers of the loads are obligatorily numbers that are rising by lane but not necessarily consecutive (due to the definition of the achievable sequence to be given).
It may be recalled that each lane corresponds to an injection flow represented as a FIFO column attached to the collector, with its injection point defined by a black dot on the diagrams.
The FIFO list of the loads taken into account in a lane for a fixed configuration of the system sets the order of the loads waiting at the injection point of this lane in accordance with the following conditions:
A work batch corresponds to the set of loads of the FIFO list of all the lanes (it is the set L of n loads). However, these loads correspond to the static photograph of our system at a given instant, complying with the rules of the preceding paragraph. The loads present in the system at this instant, which do not comply with the rules of filling of FIFO lists, will be assigned later to another batch. Once the loads of the batch are all allotted, the injection dates for this batch are computed. The injection of these loads is done as and when the time passes, in complying with the injection dates computed beforehand. The system develops in the course of time, without again calling the injection date computation algorithm, although new loads are eligible under the rules of filling of the FIFO lists or even if new loads appear in the system.
All these injection dates are computed in order to succeed in placing each load of the batch at a reserved place on the conveyor, in complying with the order of the desired final sequence, while at the same time minimizing the vacant spaces. Let p designate the last place reserved for the last load of this batch given by the order of the sequence. After this place p, the collector is vacant. It is the time at which this last place p (which can be still vacant) passes below the first injection flow (first lane) that a new batch will be defined.
The following batch will be built in the same way, but on a new static photo of the system at this fixed instant (with, as its first unoccupied location, the span of the collector attached to this last place p).
It must be noted, in one particular implementation, that if a new batch is defined before the preceding batch has been entirely executed, the last loads of the exit sequence of the preceding batch can be considered for the new batch (following batch). In this case, if a load at the position i in the exit sequence is put back into the next batch, then so too are all the loads having positions greater than i). However, it is worthwhile to take up the loads again only if the desired final sequence has changed. In this case, the last place p considered will be the place of the last load not taken up in the next batch. For the loads that are taken up, the injection dates already defined in the preceding batch will be obsolete and replaced by dates of injection computed for the next batch.
In the example illustrated in
The processing of each batch is done continuously and in series (batch1, batch2, etc.). The processing of a batch is a static computation of all the dates of injection of the loads composing this batch. The linking and the building of these batches provides a comprehensive solution to the problem of merging the incoming flows into one outgoing flow in the warehouses, which is a dynamic problem.
So long as the time span of the collector awaiting the highest sequence number (in this case no 9, surrounded by a circle in
When the last marked span of the last load of the sequence of the first batch arrives before the lane a1, it is the signal for building the next batch. This batch is constituted by all the valid loads of each FIFO list of each lane according to the rules explained further above.
The algorithm for computing the static injection dates is applied to this new batch in considering the unoccupied part of the collector (to the right of the place reserved for the load numbered 9 of the previous batch). The injection dates are computed as a function of a time scale, the origin of which corresponds to the first injection of a load of the new batch.
The configuration of the static system, taken at the “Time 5” as can be seen in
The date 0 is fixed by simultaneous injection of two new loads numbered 1 and 4 (into the lanes a2 and a1 respectively). Since this origin of time, the algorithm gives a date of injection T(u) for each of the six new loads u of this new batch.
L′={1,4} and t0=max{Δ1+1−σ(4),Δ2+1−σ(1)}=max{3,3}=3
T(1)=t0+σ(1)−1−Δ2=0
T(2)=t0+σ(2)−1−Δ2=1
T(3)=t0+σ(3)−1−Δ3=5
T(4)=t0+σ(4)−1−Δ1=0
T(5)=t0+σ(5)−1−Δ2=4
T(6)=t0+σ(6)−1−Δ1=2
7.2.4 Link Between the Injection Dates of a Batch and the Real Time that Elapses
Each load of each batch will be given an injection date as a function of an origin of time that is well specified in relation to the static system. These injection dates must be placed at the right instant in the dynamic configuration to be consistent with the dynamic solution.
A time scale common to all the batches makes it possible to link the injections of all the loads into the dynamic system. The time unit of this time scale is the “time span” of the collector, as defined further above. Let “Time” be the time derived from this common time scale, with the time 0 representing the starting date of the operations in the system.
The injection dates given by the algorithm must be repositioned correctly in this common time scale. To this end, it is necessary to find the time-related correspondence, in the dynamic system, of the situation described at the date 0 of the batch. This means that it is necessary to obtain a correspondence between the date 0 of the batch and the Time of the common scale truly enabling the first injection of the load of this batch. It is then necessary to shift all the injection dates of this batch exactly this time.
To this end, it is necessary to know the Time (also called “Tb”) at which the algorithm call has been launched and the (or at least one of the) first load or loads of the batch to be injected at the earliest on the collector, which shall be called σ*. The date 0 of the batch corresponds to the action of injecting this load σ*=ai(j), and it is done really by the dynamic system exactly σ(σ*)+Δ1,*time spans after the call.
Returning to the present example, it is necessary to add to each injection date computed by the algorithm for the new batch (for all t u∈L,T(u)), the actual date (algorithm call date) in this case the Time 5 (i.e. Tb=5) plus the position of the first injected load of the new batch injected into the new sequence (in this case it is the load 1, hence we need to add σ(1)=1) plus the distance between the lane a1 and the one containing this first injected load (in this case Δ1,2=3). In noting that the load 4 of the new batch is also injected first into the collector (at the same time as the load 1 of the new batch), we could have chosen it and added σ(4)+Δ1,1=4; this really amounts to the same thing as adding σ(1)+Δ1,2=1+3=4.
For the dynamic application, we carry out a linear transformation of the injection time as follows:
T(1)+5+4=0+5+4=9
T(2)+5+4=1+5+4=10
T(3)+5+4=5+5+4=14
T(4)+5+4=0+5+4=9
T(5)+5+4=4+5+4=13
T(6)+5+4=2+5+4=11
In this case, the earliest date of the first load of the new sequence passing in front of ak will be exactly Tb+σ(u*)+Δ1−Δi*+t0, with u*=ai*(1) the first load of the new sequence to be injected into the collector (being not necessarily the first load of the new sequence). Now, we know that t0 is a maximum attained exactly by this load u*, giving
Thus, we know that the first load of the new sequence will pass in front of ak at Tb+σ(u*)+Δ1−Δi*+t0=Tb+σ(u*)+Δ1−Δi*+Δi*+1−σ(u*)=Tb+1+Δ1, in the common time scale.
An equivalent way of giving the injection times in the common time scale is, by definition, to give the algorithm t0=Tb+1+Δ1, when we obtain knowledge of the system exactly at an instant Tb=(ulast)−Δ1+Δi
In the above example, the instant Tb=5 corresponds exactly to the condition and we could therefore have called the algorithm with t0=Tb+1+Δ1=5+1+6=12 (rather than 3) and we could have directly had the injection times expressed in the common time scale.
Ultimately, our system can be represented as is shown by
We shall assume that there now exists at least one disturbing flow (of disturbing loads) already present in the collector. These disturbing loads are part of none of the injection flows (incoming flows). Therefore, they are not ordered in the desired exit sequence of the injection flows. These disturbing loads disturb the introduction of the payloads contained in the injection flows because they occupy places on the collector. It is necessary to take account of these obstructions which block the injection of the payloads from time to time. In addition, if these disturbing loads disappear from the collector between the injection lanes, that can create vacant spaces in the exit flow from the collector. Our goal is always to comply with an exit sequence in maximizing the throughput of the collector and thus minimizing these vacant spaces.
To achieve this goal, we shall use non-valid lists of dates to be exploited with the modelling of the Job Shop seen further above.
The following table gives new notations needed for the part that follows (summary of notations for the disturbing flows).
The following table gives the new notations for the disturbing flows.
8.1 Modelling of the System with a Non-Controlled Disturbing Flow
The disturbing loads of the disturbing flow block the injection of a payload into the collector when they pass in front of the injection lanes. It is therefore necessary to compute the non-valid dates not valid for an injection of a payload for each lane. We now seek to compute the new dates of injection of the payloads in taking account of the non-controlled disturbing flow (over which, by definition, we assume that we have no control whatsoever). We note that there can henceforth be unoccupied spaces in the exit flow, and we shall nevertheless seek the optimal minimizing of these unoccupied spaces.
We can take account of a non-controlled disturbing flow, comprising disturbing loads that remain on the collector, thus passing in front of all the lanes and forming part of the final flow of the collector (mixed with the payloads of the injection flows). We can also take account of a non-controlled disturbing flow comprising disturbing loads present on the collector but disappearing between the injection lanes, thus creating unoccupied locations in front of certain lanes but not all of them. We can also take account of the case of a mixture of these types of non-controlled disturbing flows, as well as disturbing loads arriving and getting distributed between the lanes. Everything can be envisaged, and we can even take account of an unspecified obstruction on one or more spans of the collector (an obstruction being not obligatorily a disturbing load but being capable also of being a place of the collector that is damaged, reserved, etc.).
In any case, the idea is to take account of the disturbing loads and/or other obstructions to compute the dates not valid for an injection of a payload of a lane. The non-valid dates are obtained by computing the instants of passage of each obstruction (i.e. each disturbing load of the disturbing flow or any other obstruction) in front of this injection lane. Let Ui denote the set of non-valid dates where the lane ai cannot inject a payload because of the disturbing loads and/or any unspecified obstructions of the time spans of the collector.
8.1.2 Idea of the Solution for Lanes that are Consecutively Well Distributed
This Job Shop scheduling problem, with a list of non-valid dates for each machine, can be resolved by following almost the same steps as those of the paragraph 6.2.1.
Here is the approach in the particular case of lanes well distributed by conveyor spans.
The real dates of injection of the payloads on the collector are deduced directly from the start of the first operation of each job. The time unit used is the one defined further above.
Based on the above paragraph, this is the approach followed in the general case to compute the real dates of injection during the merger of several flows comprising incoming flows (injection flows) and (at least) one non-controlled disturbing flow.
The real dates of injection of the payloads into the collector are deduced directly from the start of the first operation of each job. The time unit used is the one defined further above.
NOTE: The presence of non-controlled disturbing flows does not always enable a flow without vacant space on the collector. With this method, we maximize the throughput of the collector without guarantee of maximality.
The algorithm 3 here below computes the dates of injection of the payloads in taking account of the disturbing flow that takes the form of the dates of prohibition of injection by lane.
The date 0 corresponds to the first load injected into the collector at the earliest. The date t0 is always the date at which the first load of the sequence passes in front of the lane ak. The general formula for
remains valid if there is no conflict with the disturbing flow during the injection of the first load of the sequence.
The algorithm 3 gives the date of injection of each load in taking account of the disturbing flow and in correcting the date t0 if necessary. The disturbing flow is taken into account by preliminary computation of the set Ui, i=1 . . . k giving the dates of passage of each disturbing load of this disturbing flow in front of the lane ai. These dates are therefore prohibited dates of injection (also called dates not valid for a payload injection).
In this algorithm, we use the simplified notation “u=σc=ai(j)∈L” to define a load u corresponding to the cth load of the sequence σ, also defined by its position j in the lane ai.
Let us look at a non-controlled disturbing flow already present on the collector, not taken into account by the desired sequence finally because the disturbing loads will all disappear before the last injection lane. This is the case for example in the context of
Let us take a flow F of n′ disturbing loads already present in the collector and to exit the collector between the injection lanes. This disturbing flow, called a return flow, corresponds to the loads that have to return to stock in the automated system (PTS). These disturbing loads must indeed pass in front of one or more injection lanes. For each disturbing load p of this return flow (disturbing flow), gp (and lp respectively) denote the number of the first lane (and the last lane respectively) in front of which the disturbing load p passes. We shall see two methods enabling the computation of the non-valid injection dates (Ui), induced by the return flow as a function of the known data.
In this particular embodiment, gp=1 and lp<k, for every load p of the return flow specific to the automated system (PTS). We shall give however the general solution with the notations gp and lp.
Then, the instants tr, tr+σ′(σ′1, σ′2), . . . , tr+σ′(σ′1, σ′n′) are congested for the machine M1 and form U1.
Let us return to the configuration of the example of paragraph 6.2.2.
Let us take k=4 lanes comprising two or three payloads. Each payload is identified by a unique sequence number as a function of the exit sequence σ=(1,2,3,4,5,6,7,8,9). This is an achievable sequence. We know the distances from each lane to the last one: Δ1=12, Δ2=7, Δ3=4 and Δ4=0.
As illustrated in
We show a state of the system at the date 0, when the first payload of the batch will be injected into the first unoccupied place of the collector. In the diagram, an unoccupied position of the collector is vacant, and the crosses indicate the positions taken by the payloads of the preceding batch and the letters denote the disturbing loads of the disturbing flow. The position of the disturbing flow at the date 0 enables us to deduce the following pieces of information: δA=13, δB=14 and δC=18.
The disturbing load B obliges the payload 4 to shift in time by one position and will leave a vacant space in the final flow of the collector. Then, the disturbing flow C obliges the payload 7 to shift by yet another position, leaving a vacant space later in the final flow of the collector.
8.2 Modelling of the System with a Controlled Disturbing Flow
We have seen that when the disturbing flow was non-controlled, it gave rise to vacant spaces in the final flow of the collector. It is therefore worthwhile to control the disturbing flow to avoid these vacant spaces. We could thus prioritize the loads of the injection flows over the loads of the disturbing flows and be able to make the disturbing flows pass into the unoccupied or free spaces left by the injection of the different lanes.
We now assume that we can control the disturbing flow. This amounts to achieving mastery over the injection of the disturbing loads of a disturbing flow, and we must decide the date (denoted as startp) at which the disturbing load p is injected before the lane a1 so as not to disturb the outgoing flow (outgoing flow formed by the merger of the injection flows), i.e. in not creating any vacant space in the exit flow.
We shall first compute the dates of injection of the payloads coming from the lanes, as if they were no disturbing flows (cf. Section 6). It is these injection dates that we shall give as the dates unavailable (Ui) for a disturbing load passing in front of a lane (ai). Then, taking account of the list of non-valid dates, we shall compute the injection of the loads of the disturbing flow. To this end, in the order of arrival of the disturbing loads, we schedule each of their passages in front of the lanes at the earliest time, i.e. as soon as these dates of passage into the respective machines fall on free dates.
The algorithm 4 described in detail here below gives the injection dates of the payloads as well as the control of the disturbing flow. The loads to be injected constitute the final flow of the collector. Their injection is decided without taking account of the disturbing flow. Then, we shall determine when to let through the loads of the disturbing flow in considering this time that the injected payloads play the same role as the non-controlled flow in the algorithm 3 here above. Thus, we can use the same technique as here above with the computation of the sets
Vi, i=1 . . . k giving the dates of passage of each payload of the injected flow in front of the lane at. These dates are therefore injection dates prohibited for the disturbing loads.
It may be recalled that σ′p,p′ gives the distance between the disturbing loads p and p′ at the date 0 and tr gives the date, without waiting, of arrival of the 1st load of the disturbing flow in front of the lane number a1.
In this algorithm, we use the simplified notation “u=σc=ai(j)∈L” to define a load u corresponding to the cth load of the sequence σ, also defined by its position j in the lane ai.
Let us take the example common to all the previous cases to be able to compare the final solutions. Let k=4 lanes comprising two or three loads. Each load is identified by a single sequence number as a function of the exit sequence σ=(1,2,3,4,5,6,7,8,9). This is an achievable sequence. We know the distances from each lane to the last one: Δ1=12, . . . , Δ2=7, Δ3=4 and Δ4=0. The disturbing flow is composed of the loads A, B, C such that lA=2, lB=2, lC=3, gA=gB=gC=1,δA=13, δB=14 and δC=18.
This time, the disturbing flow is controllable. We can see in
The solution of the algorithm taking account of the disturbing flow amounts to sliding the disturbing loads into the grey boxes, left empty by the pure injection solution. The load A is allowed to pass as soon as it arrives at the control point of the disturbing flow while the load B is retained for one time unit. This wait enables the disturbing load B to be made to pass into the free spaces of the injections, just before the load 5 is injected. This is also the case with the load C and the load 8 of the sequence.
8.3 Modelling the System with a Non-Controlled Disturbing Flow and a Controlled Disturbing Flow
Should there be at the same time at least one non-controlled disturbing flow and at least one controlled disturbing flow, we proceed thus.
We differentiate the non-controlled disturbing loads from the controlled disturbing loads as follows:
Let δ′p designate the distance between each disturbing load p∈S and the last lane ak at the date Tb and let g′p and l′p respectively designate the number of the first and last lane in front of which the disturbing load p must pass.
Finally, the sets Ui, i=1 . . . k, give the dates of unavailability of passage in front of the lane ai for the payloads.
Let δp designate the distance from each disturbing load p∈F to the last lane ak at the date Tb and let gp and lp respectively denote the number of the first and last lane in front of which the disturbing load p must pass.
Finally, the sets Vi, i=1 . . . k, give the dates of unavailability of passage in front of the lane ai for these controlled disturbing loads.
The algorithm 5 provides a detailed view here below of the dates of injection of the payloads as well as the control of the disturbing flow, in taking account of the non-controlled disturbing flow.
Since the travel time is critically important to obtaining the highest possible production rate, it is very important, in logistics, to being capable of combining several incoming flows. Using all the mechanical capacities of each system and therefore maximizing the throughput of such a collector is crucial in avoiding loss of time in customer order picking for example.
We have attained the optimal throughput by injecting the loads at the earliest in a synchronized manner. We have especially attained the maximum capacities of the collector when it is dedicated to the injection flows. In addition to the modelling and mathematical resolution, we have extracted a formula enabling the direct computation of the dates of injection of each load. These results are given to comply with a final exit sequence of the loads once they are all on the collector, thus making it possible to combine the optimization of a speed and of a sorting operation.
We have also discussed the management of several types of flows on the collector, in using the term “disturbing flow” to denote a flow different from the injection flow. We are able to compute the dates of injection using an algorithm that takes account of this disturbing flow when it is non-controlled. However, the throughput is optimal without guarantee of maximality. Indeed, such a non-controlled disturbing flow does not make it possible to recover a space left by a disturbing flow that would have gone out of the collector between the injection lanes.
We have also proposed a solution in which the disturbing flow is controlled. Another algorithm has been given to make the controlled disturbing flow pass in such a way as to prioritize the maximum throughput of the collector once all the injection lanes have passed. The control of this controlled disturbing flow enables a maximum throughput of the injection flows once on the collector when all the loads of the controlled disturbing flow disappear before the last injection lane. If not, the remaining disturbing flows are included in the final flow of the collector and inserted into the sequence without spaces.
An algorithm has also been given to manage at least one non-controlled flow (obstructions that are not obligatorily disturbing loads) and, at the same time, at least one controlled flow (disturbing loads).
The proposed solution is a method of merging, within a logistical warehouse, k incoming flows of payloads, transported respectively by k conveyors called lanes ai with i∈{1, . . . , k}, into one outgoing flow of payloads transported by another conveyor called a collector.
The method of merger is executed by a control system. This is for example a central warehouse control system or WCS.
At initialization, the code instructions of the computer program are for example loaded into the live memory 92 and then executed by the processor of the processing unit 91, to implement the method of merger of the invention (according to any one of the different embodiments described here above). The processing unit 91 inputs pieces of information 94 pertaining to the incoming flows. The processor of the processing unit 91 processes the information 94 and generates at exit instructions or commands 95 used to control (command) different elements included in the system, especially the lanes, the collector, the control means, etc.
This
Should the control system be carried out with a reprogrammable computing machine, the corresponding program (i.e. the sequence of instructions) can be stored in a storage medium that it detachable (such as for example a floppy disk, a CD-ROM or a DVD-ROM) or non-detachable, this storage medium being partially or totally readable by a computer or a processor.
Number | Date | Country | Kind |
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1912231 | Oct 2019 | FR | national |
1912777 | Nov 2019 | FR | national |