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.
154
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.
95
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).
92
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
Mathematical Modeling and Optimization of Energy-Conscious Flexible Job Shop Scheduling Problem With Worker Flexibility
TL;DR: This paper addresses the dual-resource constrained flexible job shop scheduling problem (DRCFJSP) with minimizing energy consumption and proposes an efficient variable neighborhood search (VNS) algorithm, which is a very competitive algorithm for the energy-conscious DRCfJSP.
A heuristic algorithm for the distributed and flexible job-shop scheduling problem
TL;DR: This paper studies the distributed and flexible job-shop scheduling problem (DFJSP) which involves the scheduling of jobs (products) in a distributed manufacturing environment, under the assumption that the shop floor of each factory/cell is configured as a flexible job shop.
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More MILP models for integrated process planning and scheduling
TL;DR: Some novel MILP models for integrated process planning and scheduling in a job shop flexible manufacturing system are developed that are able to express and utilise flexibilities contained in network graphs, and hence have the power to solve network graph-based instances.
42
Multi-level job scheduling in a flexible job shop environment
Hong-Bum Na,Jinwoo Park +1 more
TL;DR: In this article, a scheduling problem with multi-level job structures in a flexible job shop environment is studied, where the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates.
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Large scale flexible scheduling optimization by a distributed evolutionary algorithm
TL;DR: This paper considers the large scale flexible scheduling problem and treats the expectation of makespan as the objective function and proposes a distributed cooperative evolutionary algorithm (dcEA) applied on Apache Spark that has better performance and lower computational complexity.
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