Analysis of Tabu List Length on Job Shop Scheduling Problem

Abstract

Tabu search is one of the meta-heuristics methods that can solve job shop scheduling problem because it has the ability to direct other methods to exit or avoid from local optimal solutions by utilizing the memory structure that records the trace of the search process that has been done that called tabu list. The size of tabu list is too small causes the local optimum and the size is too large causes the algorithm does not work effectively and will be slower for finding the best solution. In this research, the authors analyse the influence of the length of tabu list on the performance of tabu search algorithm on job shop scheduling problem. The size of tabu list is obtained by finding the median value of the minimum tabu list and the size of tabu list that obtained from the method of tabu search. The result of experiment shows that the length of tabu list that obtained by finding the median value is ideal for the small and large size job.