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 modelling and optimisation of energy-conscious hybrid flow shop scheduling problem with unrelated parallel machines
TL;DR: The results demonstrate that the IGA is more effective than the genetic algorithm (GA), simulating annealing algorithm (SA) and migrating birds optimisation algorithm (MBO) and within no more than 10% of the running time of the best MILP model.
134
An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem
TL;DR: A novel efficient approach based on gravitational search algorithm (GSA) is proposed to solve the PPDLBP, and a mathematical model of this problem is established, which is to achieve the maximisation of profit for dismantling a product in DLBP.
133
Optimisation of distributed manufacturing flexible job shop scheduling by using hybrid genetic algorithms
Hao-Chin Chang,Tung-Kuan Liu +1 more
TL;DR: The experimental results indicate that the proposed HGA approach for solving the distributed and flexible job-shop scheduling problem (DFJSP) is considerably robust, outperforming previous algorithms after 50 runs.
125
Constraint programming for solving various assembly line balancing problems
Yossi Bukchin,Tal Raviv +1 more
TL;DR: In this paper, the constraint programming (CP) approach is applied for the simple assembly line balancing problem (SALBP) as well as some of its generalizations, and the proposed formulations are conversions of well-known mixed integer programming (MILP) formulations to CP, along with a new set of constraints that helps the CP solver to converge faster.
106
A multi-objective iterated local search algorithm for comprehensive energy-aware hybrid flow shop scheduling
TL;DR: A new multiphase iterated local search algorithm (ILS) is developed to determine a three-dimensional Pareto front regarding three objectives: makespan, total energy costs and peak load, which is proven to be suitable in purposeful search in the solution space, which allows practical decision support.
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