Development and Evaluation of Improved Tabu Search

Abstract

An improved search method has been developed by incorporating an agenda (solution pool) mechanism into the tabu search framework and it was evaluated through application to a job shop scheduling problem. The mechanism facilitates search from a solution in the agenda, while neighbor solutions being sequentially searched by the conventional tabu search. The tabu-list is dynamically synthesized for a selected solution, since the individual history of the solution is quite different from the actual search process.
The bench mark problem was the shortest completion of 6 jobs with 6 machines. Case studies with 50 runs were done for the developed method and conventional search methods. The results reveal that optimal solutions are more frequently (62%) obtained by the developed method than by a conventional tabu search (36%) and a genetic algorithm (46%).