Title: Machine cell formation: using genetic algorithm-based heuristic considering alternative route

Authors: Kamal Deep; Pradeep K. Singh

Addresses: Department of Mechanical Engineering, Guru Jambeshwar University of Science and Technology, Hissar – 125 001, HR, India ' Department of Mechanical Engineering, Sant Longowal Institute of Engineering and Technology, Longowal – 148 106, PB, India

Abstract: In this paper, genetic algorithm-based heuristic is proposed to solve the cell formation problem. The proposed algorithm selects the optimum part route with certain set of machines before clustering the machine cell. A heuristic is applied within the genetic algorithm for assignment of parts to independent cell. Further, trade-off between part inter-cell movement and machine duplication is permitted to optimise the machine cell design. The proposed model simultaneously considers relevant production data such as production volume, alternative part process route, operation sequence and process time. Conventional optimisation method for the optimal cell formation problem requires significant amount of time and large memory space. Hence, a genetic algorithm-based heuristic method has been developed for solving the proposed model. To evaluate the computational performance of the proposed approach, the algorithm is tested on four benchmark problems collected from literature. The results approve the effectiveness of the proposed method in the manufacturing cell formation.

Keywords: cellular manufacturing; operation sequences; alternative routing; genetic algorithms; machine cell formation; manufacturing cells; cell design; production volume; process time; optimisation.

DOI: 10.1504/IJOR.2015.070863

International Journal of Operational Research, 2015 Vol.24 No.1, pp.83 - 101

Received: 14 Feb 2013
Accepted: 30 Aug 2013
Published online: 31 Jul 2015 *

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