An MILP for scheduling problems in an FMS with one vehicle

Caumond, Anthony; Lacomme, Philippe; Moukrim, Aziz; Tchernev, Nikolay

doi:10.1016/j.ejor.2008.03.051

Cited by 79 publications

(36 citation statements)

References 25 publications

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“…For example, the scheduling problems are investigated for automatic guided vehicle (AGVs) in flexible manufacturing systems (FMSs) with the mixed integer programming. 7 However, the method is only suitable for small or medium-size systems, because the computational complexity sharply increases with the number of decision variables and it must take more time to find optimal solutions. Moreover, when it comes to large-size systems, it is quite difficult to solve the scheduling problems to optimum.…”

Section: Introductionmentioning

confidence: 99%

An adaptive SVM-based real-time scheduling mechanism and simulation for multiple-load carriers in automobile assembly lines

Zhou

2017

Int. J. Model. Simul. Sci. Comput.

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Multiple-load carriers are widely introduced for material delivery in manufacturing systems. The real-time scheduling of multiple-load carriers is so complex that it deserves attention to pursue higher productivity and better system performance. In this paper, a support vector machine (SVM)-based real-time scheduling mechanism was proposed to tackle the scheduling problem of parts replenishment with multiple-load carriers in automobile assembly plants under dynamic environment. The SVM-based scheduling mechanism was trained first and then used to make the optimal real-time decisions between "wait" and "deliver" on the basis of real-time system states. An objective function considering throughput and delivery distances was established to evaluate the system performance. Moreover, a simulation model in eM-Plant software was developed to validate and compare the proposed SVM-based scheduling mechanism with the classic minimum batch size (MBS) heuristic. It simulated both the steady and dynamic environments which are characterized by the uncertainty of demands or scheduling criteria. The simulation results demonstrated that the SVM-based scheduling mechanism could dynamically make optimal real-time decisions for multiple-load carriers and outperform the MBS heuristic as well.

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Section: Introductionmentioning

confidence: 99%

An adaptive SVM-based real-time scheduling mechanism and simulation for multiple-load carriers in automobile assembly lines

Zhou

2017

Int. J. Model. Simul. Sci. Comput.

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“…To analyze the impact of DL control policies on scheduling performance, we implement a least-cost strategy that controls the flow of jobs [55], [56] in order to guarantee a DL-free design of the system. It restricts the number of active jobs (work-in-process) that flow within the system simultaneously so as to reduce resource competition.…”

Section: Table II Places and Their Meaningsmentioning

confidence: 99%

Deadlock-Free Scheduling Method for Flexible Manufacturing Systems Based on Timed Colored Petri Nets and Anytime Heuristic Search

Baruwa

Piera

Guasch

2015

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-This paper addresses the deadlock (DL)-free scheduling problem of flexible manufacturing systems (FMS) characterized by resource sharing, limited buffer capacity, routing flexibility, and the availability of material handling systems. The FMS scheduling problem is formulated using timed colored Petri net (TCPN) modeling where each operation has a certain number of preconditions, an estimated duration, and a set of postconditions. Based on the reachability analysis of TCPN modeling, we propose a new anytime heuristic search algorithm which finds optimal or near-optimal DL-free schedules with respect to makespan as the performance criterion. The methodology tackles the time-constrained problem of very demanding systems (high diversity production and make-to-order) in which computational time is a critical factor to produce optimal schedules that are DL-free. In such a rapidly changing environment and under tight customer due-dates, producing optimal schedules becomes intractable given the time limitations and the NP-hard nature of scheduling problems. The proposed anytime search algorithm combines breadth-first iterative deepening A * with suboptimal breadth-first heuristic search and backtracking. It guarantees that the search produces the best solution obtained so far within the allotted computation time and provides better solutions when given more time. The effectiveness of the approach is evaluated on a comprehensive benchmark set of DL-prone FMS examples and the computational results show the superiority of the proposed approach over the previous works.Index Terms-Anytime heuristic search, deadlock-free, flexible manufacturing systems (FMS), Petri nets (PN), reachability analysis, scheduling.

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“…The following assumptions and technical and managerial constraints are mostly taken into considerations in FMS studies with realistic implementations (Luh, 1998;Caumond et al, 2009;Herrero-Perez and Martinez-Barbera, 2010;Berger et al, 2010).…”

Section: Assumptions and Constraintsmentioning

confidence: 99%

“…Limiting the number of products is a measure to avoid internal deadlocks (Caumond et al, 2009). Herein, we consider the case where a transport device is associated to a product during all its production time.…”

Section: Assumptions and Constraintsmentioning

confidence: 99%

Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach

Rey

Bonte

Prabhu

et al. 2014

Simulation Modelling Practice and Theory

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An MILP for scheduling problems in an FMS with one vehicle

Cited by 79 publications

References 25 publications

An adaptive SVM-based real-time scheduling mechanism and simulation for multiple-load carriers in automobile assembly lines

An adaptive SVM-based real-time scheduling mechanism and simulation for multiple-load carriers in automobile assembly lines

Deadlock-Free Scheduling Method for Flexible Manufacturing Systems Based on Timed Colored Petri Nets and Anytime Heuristic Search

Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach

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