Title: A hybrid genetic-goal programming approach for improving group performance in cell formation problems

Authors: Barnali Chaudhuri; R.K. Jana; Dinesh K. Sharma; P.K. Dan

Addresses: Department of Business Management, Indian Institute of Social Welfare and Business Management, India ' Operations and Quantitative Methods Area, Indian Institute of Management Raipur, Atal Nagar, Raipur, CG 493661, India ' Department of Business, Management and Accounting, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA ' Rajendra Mishra School of Engineering Entrepreneurship, Indian Institute of Technology Kharagpur, WB 721302, India

Abstract: This paper proposes a hybrid genetic-goal programming approach to improve group performance in cell formation problems in manufacturing systems. The problem is formulated mathematically as a multi-objective programming problem. A proposed genetic algorithm (GA) is used to solve the problem. The chromosomes of the GA represent a combination of machines and parts. The proposed approach improves group performance by considering group efficacy as the performance measure. A software package corresponding to the proposed approach is developed in C# has a user-friendly GUI. Thirty problem instances of varying sizes prove the superiority of the approach in terms of group efficacy by avoiding duplicity in the allocation of parts into machines.

Keywords: cellular manufacturing; group efficacy; hybrid genetic algorithm; HGA; goal programming.

DOI: 10.1504/IJAOM.2020.112734

International Journal of Advanced Operations Management, 2020 Vol.12 No.4, pp.377 - 395

Accepted: 28 Jul 2020
Published online: 01 Feb 2021 *

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