A Free-Slack-Based Genetic Algorithm for the Robotic Cell Problem with Controllable Processing Times

Mohammed Al-Salem (), Mohamed Haouari (), Mohamed Kharbeche () and Wael Khallouli ()
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Mohammed Al-Salem: Qatar University
Mohamed Haouari: Qatar University
Mohamed Kharbeche: Qatar University
Wael Khallouli: Qatar University

Chapter Chapter 4 in Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling, 2016, pp 77-93 from Springer

Abstract: Abstract We present a novel genetic algorithm for the Robotic Cell Problem with controllable processing times. This challenging problem arises in an automated production cell that consists of m consecutive machines as well as a material handling robot. The problem requires finding the operations processing times, job assignment, and robot movements. The objective is to minimize the makespan subject to a budget constraint. We describe a free-slack-based genetic algorithm for the linear resource consumption case. We present the results of a computational study and we provide evidence that the proposed algorithm consistently outperforms MIP-based heuristics from the literature.

Keywords: Flexible manufacturing; Robotic cell scheduling; Controllable processing; Genetic algorithms; Makespan (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-26024-2_4

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DOI: 10.1007/978-3-319-26024-2_4

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