Journal Article10.1016/J.CIE.2020.106347
Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem
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TL;DR: The results show that the sequence-based MILP model is the most efficient one, and the proposed CP model is effective in finding good quality solutions for the both the small-sized and large-sized instances.
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About: This article is published in Computers & Industrial Engineering. The article was published on 01 Apr 2020. The article focuses on the topics: Constraint programming & Job shop scheduling.
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Citations
Learning-enabled Flexible Job-shop Scheduling for Scalable Smart Manufacturing
TL;DR: This work introduces a novel graph-based DRL method, named the Heterogeneous Graph Scheduler (HGS), which leverages locally extracted relational knowledge among operations, machines, and vehicle nodes for scheduling, with a graph-structured decision-making framework that reduces encoding complexity and enhances scale generalization.
An approximate evaluation method for neighbourhood solutions in job shop scheduling problem
TL;DR: In this article , an approximate evaluation method for neighbourhood solutions in job shop scheduling problems is proposed by exploring domain knowledge in neighbourhood solutions, and according to the domain knowledge, the evaluated value of the neighbourhood solution is the exact value under certain conditions.
References
Routing and scheduling in a flexible job shop by tabu search
TL;DR: A hierarchical algorithm for the flexible job shop scheduling problem is described, based on the tabu search metaheuristic, which allows to adapt the same basic algorithm to different objective functions.
1.1K
On the Job-Shop Scheduling Problem
TL;DR: This formulation of discrete linear programming seems, however, to involve considerably fewer variables than two other recent proposals and on these grounds may be worth some computer experimentation.
Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems
Vipul Jain,Ignacio E. Grossmann +1 more
TL;DR: The goal of this paper is to develop models and methods that use complementary strengths of Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) techniques to solve problems that are otherwise intractable if solved using either of the two methods.
Mathematical modeling and heuristic approaches to flexible job shop scheduling problems
TL;DR: A mathematical model and heuristic approaches for flexible job shop scheduling problems (FJSP) are considered and it is concluded that the hierarchical algorithms have better performance than integrated algorithms and the algorithm which use tabu search and simulated annealing heuristics for assignment and sequencing problems consecutively is more suitable than the other algorithms.
415
A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times
Eva Vallada,Rubén Ruiz +1 more
TL;DR: After an exhaustive computational and statistical analysis it can be concluded that the proposed method shows an excellent performance overcoming the rest of the evaluated methods in a comprehensive benchmark set of instances.
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