A TABU SEARCH ALGORITHM TO MINIMIZE TOTAL WEIGHTED TARDINESS FOR THE JOB SHOP SCHEDULING PROBLEM

This research presents a tabu search algorithm with a restart (TSA-R) approach to minimize total weighted tardiness (TWT) for the job shop scheduling problem. Jobs have non-identical due dates. The problem belongs to the class of NP-hard problems. The TSA-R approach uses dispatching rules to obtain an initial solution and searches for new solutions in a neighborhood based on the critical paths of jobs and blocks of operations. The TSA-R applies a new diversification scheme to exploit the initial solutions and its neighborhood structures so as to overcome entrapment issues and to enhance solutions. A computational result based on standard benchmark instances from the literature is presented to show the effectiveness of the proposed tabu search algorithm.