A genetic algorithm for the distributed assembly permutation flowshop scheduling problem

This paper investigates the problem of minimizing makespan for the distributed assembly permutation flowshop scheduling problem (DAPFSP)-a new generalization of the distributed permutation flowshop scheduling problem (DPFSP). DAPFSP consists of two stages: production and assembly. The first stage is production at several identical factories. Each factory is a permutation flowshop scheduling problem with multi-machine. And the second stage is to assemble jobs produced at the first stage into final products. We proposed a genetic algorithm for this problem. An enhanced crossover strategy and three different local searches are adopted. After the exhaustive computational and statistical analysis, we can conclude that the proposed methods are robust and outperformed the existing algorithm.