Title: A review on implementation of meta-heuristic approaches for layout problems in dynamic business environment

Authors: Parveen Sharma; Sandeep Singhal

Addresses: Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra-136119, Haryana, India ' Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra-136119, Haryana, India

Abstract: Arrangement of the facilities on shop floor in industries termed as facility layout planning. It is a vital issue at the premature stage while designing a manufacturing structure because it affects the total manufacturing cost considerably. The dynamic environment is such an industrial condition in which flexibility exists in the demand of the product. The purpose of this research paper is to present a review on the implementation of meta-heuristics approaches for handling the problem of facility layout in a dynamic environment. Various meta-heuristic approaches which have been implemented in facility layout planning (FLP) are discussed briefly and the percent utilisation of different approaches is analysed in various time spans. Tabu search (TS), genetic algorithm (GA), particle swarm optimisation (PSO), and ant colony optimisation (ACO) are several typically used methods by researchers for layout optimisation. In the present study, % utilisation of these algorithms has been analysed for different time span, ACO utilised by maximum researchers in the time span '2010-2015'. The present study also revealed GA has been executed by most of the researchers (25%), whereas PSO (8%) utilised by very least designers.

Keywords: dynamic environment; metaheuristics; optimisation; facility layout; layout planning; hybrid approaches; manufacturing industry; tabu search; genetic algorithms; particle swarm optimisation; PSO; ant colony optimisation; ACO.

DOI: 10.1504/IJMDA.2016.081076

International Journal of Multivariate Data Analysis, 2016 Vol.1 No.1, pp.6 - 27

Received: 25 Nov 2015
Accepted: 22 Dec 2015
Published online: 20 Dec 2016 *