An effective memetic algorithm for distributed flexible job shop scheduling problem considering integrated sequencing flexibility

Abstract

Thus far, the available works on sequencing flexibility in shop floor scheduling only consider the sequencing flexibility with serial operation constraint. However, the sequencing flexibility with discrete and hybrid operation constraints are also widely existed in the actual production and have significant impact on production efficiency. Therefore, this work proposes a distributed flexible job shop scheduling problem considering integrated sequencing flexibility (DFJSPS), in which the serial, discrete and hybrid operation constraints are considered simultaneously. A mixed integer linear programming model is proposed to solve the DFJSPS by using the CPLEX solver. Then, an efficient memetic algorithm (EMA) is designed with the objectives of minimizing makespan and total energy consumption. In the EMA, a five-layer coding method and an efficient initialization method are presented to obtain high quality initial solutions; and an efficient local search operator is designed to help the algorithm to improve its convergence speed. Comprehensive experiments show that the EMA outperforms other three well-known algorithms in most of the instances, demonstrating the superior performance of EMA for solving DFJSPS in terms of both computational efficiency and solution quality. In summary, the research fills the research gap on integrated sequencing flexibility in the field of shop floor scheduling; on the other hand, it can help production managers to obtain the efficient scheduling schemas in the decision-making systems about various types of sequencing flexibility.