An ACO algorithm for scheduling a flow shop with setup times

被引：1

作者：

Rojas-Santiago M. ^{[1
]}

Muthuswamy S. ^{[2
]}

Hulett M. ^{[3
]}

机构：

[1] Department of Industrial Engineering, Universidad Del Norte, Barranquilla

[2] Department of Technology, College of Engineering and Engineering Technology, Northern Illinois University, De Kalb, 60115, IL

[3] Department of Management Science, School of Business, University of Miami, Coral Gables, 33146, FL

来源：

International Journal of Industrial and Systems Engineering | 2020年 / 36卷 / 01期

关键词：

ACO; Ant colony optimisation; Flow shop; Makespan; Particle swarm optimisation; PSO; Scheduling; Setup time;

D O I：

10.1504/IJISE.2020.109123

中图分类号：

学科分类号：

摘要：

A flow shop scheduling problem with setup times has been studied in a food processing setting. This company packs cooking sauces and spices. The objective is to minimise the makespan (Cmax) taking the setup times into consideration. Given that this problem in NP-hard, an ant colony optimisation (ACO) algorithm has been developed to find the initial solution which is further improved using 2-opt and 3-opt local heuristic. Using Taillard's benchmark problems' processing times and randomly generated setup times, 60 problem instances were computed for 50 to 200 jobs using 10 and 20 machine scenarios. These Cmax values were compared against the results obtained through a particle swarm optimisation (PSO) metaheuristic. The results clearly show that the ACO algorithm schedules the machines consistently well to minimise the Cmax value in comparison to the PSO algorithm. © 2020 Inderscience Enterprises Ltd.. All rights reserved.

引用

页码：98 / 109

页数：11

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