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ScienceAsia 48S (2022):ID 12-20 |doi: 10.2306/scienceasia1513-1874.2022.S002

Development of a modified biogeography-based optimisation tool for solving the unequal-sized machine and multi-row configuration facility layout design problem

Saisumpan Sooncharoena, Srisatja Vitayasaka, Pupong Pongcharoena,*, Chris Hicksa,b

ABSTRACT:     An effective layout can reduce material flow distances and manufacturing lead-times, whilst increasing productivity, throughput and cost effectiveness. The facilities layout problem (FLP) is a non-deterministic polynomial-time hard problem, which means that the computational time taken to produce solutions increases exponentially with problem size. Metaheuristics are particularly suitable for solving such problems in reasonable time. Biogeography-based optimisation (BBO) is a well-known nature-inspired computing metaheuristic. Its mechanisms mimic an analogy with biogeography which relates to the migration, mutation and geographical distribution of biological organisms. This paper presents a novel BBO optimisation tool that solves the unequal area facilities layout problem to generate multi-row solutions that minimise the total material flow distance. Two novel modifications were made to the conventional BBO: the use of a Genetic Algorithm crossover operator in the migration process; and a changed method for selecting candidate solutions. The local search approaches used data on flow intensities and machine adjacencies. Experiments were conducted using five benchmark datasets obtained from the literature. The statistical analysis of the computational results indicated that the proposed mBBOs produced statistically better solutions than the conventional BBO and other metaheuristics for all datasets and converged more rapidly with comparable execution times.

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a Centre of Operations Research and Industrial Applications (CORIA), Department of Industrial Engineering, Faculty of Engineering, Naresuan University, Phitsanulok 65000 Thailand
b Newcastle University Business School, University of Newcastle upon Tyne, NE1 7RU, United Kingdom

* Corresponding author, E-mail: pupongp@nu.ac.th

Received 30 Oct 2020, Accepted 12 Jul 2021