Title: Solving industrial multiprocessor task scheduling problems using an improved monkey search algorithm

Authors: M.K. Marichelvam; M. Geetha

Addresses: Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, 626005, India ' Department of Mathematics, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu, 626001, India

Abstract: This paper addresses multiprocessor task scheduling in a multistage hybrid flowshop environment which has been proved to be strongly NP-hard. An improved monkey search algorithm (IMSA) is proposed to solve this problem. The objective is to minimise the makespan which is the completion time of all the tasks in the last stage. The proposed algorithm is tested with three types of problems. A real industrial data is first used. Then, random problem instances are generated and finally, the benchmark problems addressed in literature are also considered. In all the three cases, the results are compared with earlier reported algorithms in the literature and the computational results reveal that the proposed algorithm is competent.

Keywords: scheduling; hybrid flowshop; HFS; multiprocessor tasks scheduling; NP-hard; monkey search algorithm; MSA; makespan.

DOI: 10.1504/IJOR.2021.115418

International Journal of Operational Research, 2021 Vol.41 No.1, pp.135 - 149

Accepted: 13 Jun 2018
Published online: 02 Jun 2021 *

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