Hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times

摘要

This paper presents a hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times. The used objective function in this research consists of minimizing of the sum of total weighted squared tardiness, makespan, total weighted squared earliness and number of tardy job. Since the problem is NP-hard, we solved this problem by hybrid genetic algorithm. To validate the proposed model, the Lingo 8.0 software was used. Comparison between the results of the Lingo 8.0 and hybrid genetic algorithm shows that in larger problems (if n >10, where n is the number of jobs) the results obtained by Lingo do not have adequate efficiency and cannot be compared with the proposed hybrid genetic algorithm in terms of computational time and deviation from the minimum objective function. Test results are provided for a wide range of problem instances.