Title: Designing an incremental cellular manufacturing system by using a hybrid approach based on the genetic algorithm and particle swarm optimisation

Authors: S. Karthikeyan; M. Saravanan; S. Ganesh Kumar

Addresses: Department of Mechanical Engineering, Christian College of Engineering and Technology, Oddanchatram, India ' Sri Subramanya College of Engineering and Technology, Palani, Dindigul, India ' Department of Mechanical Engineering, RVS College of Engineering and Technology, Dindigul, India

Abstract: In every manufacturing technology the worker has a very important role in the manufacturing unit. In this paper, incremental cellular manufacturing system is to be designed for job shop into a CMS comprehensively in single run. The nonlinear programming model in incremental environment presents the variety of machine and part type to worker. The proposed model is a hybrid of particle swarm optimisation (PSO) and genetic algorithm (GA) to get an optimal solution by considering incremental cellular manufacturing design. The main advantage of the proposed model is found much more efficient than the genetic algorithm and artificial neural networks to solve the present model using meta-heuristic method.

Keywords: cellular manufacturing systems; CMS design; particle swarm optimisation; PSO; incremental environment; genetic algorithms; GAs; manufacturing cells; nonlinear programming; metaheuristics.

DOI: 10.1504/IJENM.2016.080459

International Journal of Enterprise Network Management, 2016 Vol.7 No.4, pp.322 - 333

Received: 24 Nov 2014
Accepted: 25 Mar 2015
Published online: 24 Nov 2016 *

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