Research On Firefly-Algorithm-Based Flexible Job Shop Scheduling Problem

Job shop scheduling problem has been a focus of production management and combinatorial optimization, as one of the most common problems of production scheduling, it belongs to NP-hard problems. Flexible job shop scheduling problem is more suitable for actual production, and has a much larger solution space. Through a reasonable scheduling scheme, the suitable task can be allocated to the limited resources within a reasonable period of time, thus the production cycle can be shortened, the in-process inventory of workshop can be controlled, the production delivery satisfaction rate and production efficiency can be improved, and so on. Therefore, researching an effective flexible job shop scheduling optimization methods has an important theoretical and practical significance for enterprises to achieving manufacturing modernization.In this paper, the flexible job shop problem’s characteristics are combined with production factors, the established mathematical model is suitable for the actual production process, and the firefly-algorithm-based multi-objective optimization method for flexible job shop scheduling problem is proposed. The main work is as follows:(1) The firefly-algorithm-based mathematical model for flexible job shop scheduling problem is established: In order to adapt the flexible job shop scheduling features, some of the related operations in the firefly algorithm are improved, such as the firefly position expression, encoding rules and decoding rules. The mobile rules of firefly are improved by mixing variable neighborhood algorithm and crossover rule of genetic algorithm in the mobile rules.(2) The discrete-firefly-algorithm-based single objective optimization of FJSP is in evaluation on minimized makespan. Four standard problems has been taken as tests, the test results verified the feasibility and effectiveness of the single objective flexible job shop scheduling optimization methods based on firefly algorithm proposed in this paper.(3) Established a multi-objective optimization model of flexible job shop scheduling problem based on firefly algorithm: Using the way of Pareto dominant sorting to evaluate multiple targets, and slicing the multiobjective solution set; in order to avoid the firefly population evolving to a single target direction, firefly population diversity maintaining strategy is proposed. Finally, four standard problems has been taken as tests, each of the problems have been obtained a reasonable Pareto dominant solution set, which verified that the multi-objective flexible job shop scheduling optimization methods based on firefly algorithm proposed in this paper is feasible and effective.