An Improved Immune Algorithm for Multi-objective Flexible Job-shop Scheduling

Abstract

Flexible job-shop scheduling problem derived from the job-shop scheduling problem, and is more realistic than the job-shop scheduling problem in the manufacturing enterprise. It should be utilized with high efficiency. But it is a multi-objective optimal problem. Three minimization objectives (Maximum completion time (makespan), Total workload of machines and Workload of the critical machine) are considered simultaneously. This multi-objective flexible job-shop scheduling problem is one of the hardest combinatorial optimization problems, and is a strongly NP-hard problem. To solve the multi-objective flexible job-shop scheduling problem, a quantum immune algorithm based on the quantum and immune principles is proposed. According to the analysis of the experimental results, this algorithm is feasible and effective to solve the multi-objective flexible job-shop scheduling problem. It effectively relieves some disadvantages of the quantum and immune optimization