Adaptive biogeography‐based optimisation for two‐sided mixed‐model assembly line sequencing problems

A mixed‐model two‐sided assembly line is a type of production line where a variety of large‐sized product models are intermixed and assembled. The determination of an optimal sequence of product models to feed such a line is imperative for effective shop floor management. In this paper, two conflicting objectives are optimised simultaneously, i.e. the minimisation of total setup cost and the minimisation of total utility work. Since the nature of the problem is non‐deterministic polynomial‐time hard, the biogeography‐based optimisation (BBO), which is a new biogeography inspired algorithm for global optimisation, is applied to search for Pareto frontiers. Three versions of BBO are proposed and tested against prominent algorithms, i.e. random permutation sequencing algorithm, non‐dominated sorting genetic algorithm II and discrete particle swarm optimisation, on several benchmark problems. The results show that the BBO algorithms outperform the contestant algorithms in terms of quality and diversity of the non‐dominated solutions. In addition, among three of them, BBO enhanced by an adaptive mechanism (BBO‐M) is superior to the others.