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A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

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TLDR
The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.
Abstract
In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

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Citations
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Journal ArticleDOI

Discrete hybrid cuckoo search and simulated annealing algorithm for solving the job shop scheduling problem

TL;DR: In this paper, the authors proposed a hybrid Cuckoo search and simulated annealing (CSA) algorithm for solving the job shop scheduling problem (JSSP) and compared it with six optimization-based scheduling algorithms (DABC, DGA, GWO, PSO-VNS, DWPA and DWPA).
Journal ArticleDOI

CPO: A Crow Particle Optimization Algorithm

TL;DR: A hybridization algorithm based on the PSO algorithm and CSA, known as the crow particle optimization (CPO) algorithm is proposed, which exhibits a significantly higher performance in terms of both fitness value and computation time compared to other algorithms.
Journal ArticleDOI

An effective genetic algorithm with a critical-path-guided Giffler and Thompson crossover operator for job shop scheduling problem

TL;DR: The computational results validate the enhancements accomplished by the proposed selective exchange of genetic materials, and show the superiority of the proposed algorithm over the compared works in terms of solution quality, and validate its effectiveness.
Journal ArticleDOI

Hybrid social spider optimization algorithm with differential mutation operator for the job-shop scheduling problem

TL;DR: In this article, a hybrid social-spider optimization algorithm with differential mutation operator is presented to solve the job-shop scheduling problem, which improves the exploration capabilities of the social spider optimization algorithm.
Proceedings ArticleDOI

A Discrete Wolf Pack Algorithm for Job Shop Scheduling Problem

TL;DR: Wolf pack algorithm is applied, providing a new method to solve the job shop scheduling problem, and a computational result shows that DWPA has a good performance on the time efficiency and accuracy compared with other algorithms.
References
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Journal ArticleDOI

The Shifting Bottleneck Procedure for Job Shop Scheduling

TL;DR: An approximation method for solving the minimum makespan problem of job shop scheduling by sequences the machines one by one, successively, taking each time the machine identified as a bottleneck among the machines not yet sequenced.
Journal ArticleDOI

A Computational Study of the Job-Shop Scheduling Problem

TL;DR: The optimization procedure, combining the heuristic method and the combinatorial branch and bound algorithm, solved the well-known 10×10 problem of J. F. Thomson in under 7 minutes of computation time on a Sun Sparcstation 1.
Journal ArticleDOI

Deterministic job-shop scheduling: Past, present and future

TL;DR: A subclass of the deterministic job-shop scheduling problem in which the objective is minimising makespan is sought, by providing an overview of the history, the techniques used and the researchers involved.
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The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.