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
Distributed Scheduling Problems in Intelligent Manufacturing Systems
TL;DR: The achievements and current research status in this field are analyzed, particularly swarm intelligence and evolutionary algorithms, which are used for managing distributed scheduling problems in manufacturing systems are discussed and future research directions are pointed out.
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A discrete artificial bee colony algorithm for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
TL;DR: A machine position-based mathematical model and a discrete artificial bee colony algorithm (DABC) for the DHFSP-SDST to optimise the makespan and results and statistical analyses validate that the DABC outperforms the best performing algorithm in the literature.
97
Decomposition-Based Multi-Objective Optimization for Energy-Aware Distributed Hybrid Flow Shop Scheduling with Multiprocessor Tasks
TL;DR: A mixed inter linear programming model and a Novel MultiObjective Evolutionary Algorithm based on Decomposition (NMOEA/D) are presented and proposed to address the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks.
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Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
TL;DR: In this article , three mixed-integer linear programming (MILP) models and a constraint programming (CP) model are formulated for distributed hybrid flow shop scheduling with sequence-dependent setup times (DHFSP-SDST).
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Solving energy-efficient distributed job shop scheduling via multi-objective evolutionary algorithm with decomposition
TL;DR: A mathematical model is presented and an effective modified multi-objective evolutionary algorithm with decomposition (MMOEA/D) is proposed, which outperforms other algorithms in the energy-efficient distributed job shop scheduling problem.
92
References
Iterated Greedy methods for the distributed permutation flowshop scheduling problem
TL;DR: This paper studies an extension of the well known permutation flowshop scheduling problem in which there is a set of identical factories, each one with a flowshop structure, and presents simple Iterated Greedy algorithms that have performed well in related problems.
An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem
TL;DR: Experimental results proved that the developed PSO is enough effective and efficient to solve the FJSP and the distribution of the PSO-solving method for future implementation on embedded systems that can make decisions in real time according to the state of resources and any unplanned or unforeseen events is studied.
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Mathematical models for job-shop scheduling problems with routing and process plan flexibility
TL;DR: In this paper, a mixed-integer linear programming model (MILP-1) is developed for FJSPs and compared to an alternative model in the literature (Model F) in terms of computational efficiency.
339
An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem
TL;DR: An Improved Genetic Algorithm to solve the Distributed and Flexible Job-shop Scheduling problem is proposed and has been compared with other algorithms for distributed scheduling and evaluated with satisfactory results on a large set of distributed-and-flexible scheduling problems derived from classical job-shop scheduling benchmarks.
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