An Investigation of Agent-Based Hybrid Approach to Solve Flowshop and Job-Shop Scheduling Problems

摘要

The paper investigates a possibility of combining the population learning algorithm and the A-Team concept with a view to increase quality of results and efficiency of computations. To implement the idea a middleware environment called JABAT is used. The proposed approach is validated experimentally using benchmark datasets containing instances of the two well-known combinatorial optimization problems: flow shop and job shop scheduling.