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A novel method-based reinforcement learning with deep temporal difference network for flexible double shop scheduling problem. [PDF]

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Wang X, Zhong P, Liu M, Zhang C, Yang S.
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Multiobjective flow-shop scheduling

Naval Research Logistics, 1990
Summary: Previous research on the scheduling of multimachine systems has generally focused on the optimization of individual performance measures. This article considers the sequencing of jobs through a multimachine flow shop, where the quality of the resulting schedule is evaluated according to the associted levels of two scheduling criteria, schedule
Daniels, Richard L., Chambers, Robert J.
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Proportionate Flow Shop Scheduling with Rejection

Asia-Pacific Journal of Operational Research, 2017
We consider the problem of scheduling [Formula: see text] jobs with rejection on a set of [Formula: see text] machines in a proportionate flow shop system where the job processing times are machine-independent. The goal is to find a schedule to minimize the scheduling cost of all accepted jobs plus the total penalty of all rejected jobs.
Li, Shi-Sheng, Qian, De-Liang, Chen, Ren-Xia   +2 more
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Flow Shop Scheduling with Resource Flexibility

Operations Research, 1994
This paper explores the improvements in manufacturing efficiency that can be achieved by broadening the scope of production scheduling to include both the sequencing of work and the coordination of the resource inputs required to perform work. Recognizing that some resources are inherently flexible and thus can be reassigned dynamically to processing ...
Daniels, Richard L., Mazzola, Joseph B.
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FLOW SHOP SCHEDULING WITH REINFORCEMENT LEARNING

Asia-Pacific Journal of Operational Research, 2013
Reinforcement learning (RL) is a state or action value based machine learning method which solves large-scale multi-stage decision problems such as Markov Decision Process (MDP) and Semi-Markov Decision Process (SMDP) problems. We minimize the makespan of flow shop scheduling problems with an RL algorithm. We convert flow shop scheduling problems into
ZHICONG ZHANG, WEIPING WANG, SHOUYAN ZHONG, KAISHUN HU   +3 more
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Heuristics for flow-shop scheduling

International Journal of Production Research, 1980
Existing methods are reviewed and new heuristics examined and developed for the flow-shop scheduling problem. Comparative tests are carried out using simulation methods on different sizes of problem and with different variability of processing time data.
J. R. KING, A. S. SPACHIS
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Scheduling flow shops with operators

International Journal of Production Research, 2018
This paper addresses the problem of assigning a number of operators, less than the number of machines, in a flow shop environment. We study two different problems. The first is the assignment of operators subject to a fixed job sequence; the second is on handling simultaneously the assignment of operators and the scheduling of jobs on the machines.
Imène Benkalai, Djamal Rebaine, Pierre Baptiste   +2 more
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Flow Shop Scheduling

2019
Consider scheduling tasks on dedicated processors or machines. We assume that tasks belong to a set of n jobs, each of which is characterized by the same machine sequence.
Jacek Blazewicz, Klaus H. Ecker, Erwin Pesch, Günter Schmidt, Malgorzata Sterna, Jan Weglarz   +5 more
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A contribution to the stochastic flow shop scheduling problem

European Journal of Operational Research, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gourgand, Michel, Grangeon, Nathalie, Norre, Sylvie   +2 more
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On Pinedo's Conjecture for Scheduling in a Stochastic Flow Shop

Operations Research, 1985
Pinedo has conjectured that, in a stochastic flow shop with m machines, n − 2 deterministic jobs with unit processing time, and two stochastic jobs each with mean one, the sequence minimizing the expected makespan would schedule one of the stochastic jobs first and the other last.
Suresh, S., Foley, R. D., Dickey, S. Elizabeth   +2 more
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