New multiobjective optimisation algorithms for assembly lines design

Multiobjective optimisation methods for an assembly line design problem are presented in this paper. The studied problem consists of two parts. Among a set of candidate machines, the first part of the problem aims to assign a single machine to each workstation. The goal of the second part is to size the intermediate buffers. Two objectives are taken in consideration for our design problem: the minimisation of the cost of the line and the maximisation of the throughput rate. Different new multiobjective methods are developed to solve the problem. First, a multiobjective ant colony optimisation algorithm is proposed. Then, in order to get better results, the first algorithm is coupled with a guided local search. The third method proposed for the first time to solve our problem, called L-ant, is based on a multiobjective ant colony algorithm but using the Lorenz dominance. The fourth algorithm is another new method based on genetic algorithms and the Lorenz dominance and called Lorenz-archive. In order to compare the different methods to each others and to assess their efficiency, different measuring criteria are applied on the best fronts with the non-dominated solutions.