An Agent Based Heuristic Algorithm for Uniform Parallel Machine Scheduling Problem with Tails

This study considers the uniform parallel machine scheduling problem with tails to minimize the maximal completion time. In this scheduling problem, all the machines are intelligent industrial robots and hence agent technology is introduced to realize the intelligence of the robots. The scheduling problem is described and analyzed and then an agent-based heuristic algorithm ABHA is presented, in which the problem is solved by the agents collaborating with each other. Each agent corresponds to a robot and assures that the corresponding sub-schedule is optimized. The most appropriate machine for each job is ascertained by a token-ring protocol of cooperation among the agents. The accuracy of the proposed ABHA is tested based on the data with problem size varying from 200 to 500 jobs. The computational results indicate that the average relative error of ABHA is only 0.15%, which is lower than the existing heuristic algorithm.