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 polynomialtime 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. Biogeographybased 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 multirow 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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