Flexible Job-Shop Scheduling Problem Based on Hybrid ACO Algorithm

For an enterprise to survive the fierce market competition, efficient production scheduling is a must as it improves economic efficiency and reduces cost. As an important branch of production scheduling, the flexible job-shop scheduling problem (FJSP) is a mixed blessing. It accurately reflects the characteristics of the actual production, but adds to the difficulties in problem solving. With the ant colony algorithm as the basic optimization method, this paper proposes the hybrid ant colony algorithm based on the 3D disjunctive graph model by combining the elitist ant system, max-min ant system and the staged parameter control mechanism, optimizes the FJSP problem to minimize the longest completion time, the early/delay penalty cost, the average idle time of the machine, and the production cost, and verifies the effectiveness of the model and algorithm by an example. (Received, processed and accepted by the Chinese Representative Office.)