A Hybrid Gray Wolf Weed Algorithm for Flexible Job-shop Scheduling Problem

Abstract For the flexible job shop scheduling problem with the goal of makespan, a mathematical model is established and a hybrid algorithm (GIWO) based on gray wolf and invasive weeds is proposed. In this paper, the intrusive weed optimization algorithm is embedded on the basis of the gray wolf algorithm to improve the algorithm’s global search and local search ability. And an effective initial population generation mechanism is added to improve the quality of the initial solution. A variable neighborhood search structure that adaptively changes according to the search is proposed. Finally, other improved gray wolf algorithms are compared with the algorithm in this paper through different benchmark instances. Experimental results show that the proposed algorithm performs better than the other algorithms in effectiveness and superiority. The algorithm can effectively solve the flexible job shop scheduling problem.