A tabu search algorithm for parallel machine total tardiness problem

In this study, a Tabu Search (TS) approach to the parallel machine scheduling problem is presented. The problem considered consists of a set of independent jobs to be scheduled on a number of parallel processors to minimize total tardiness. Several surveys on parallel machine scheduling with due date related objectives [1, 2, 3] reveal that the NP-hard nature of the problem renders it a challenging area for many researchers who studied various versions. However, most of these studies have the assumption that jobs are available at the beginning of the scheduling period, which is an important deviation form reality. Here, as well as distinct due dates and ready times, features such as sequence dependent setup times and different processing rates for machines are incorporated into the classical model. These enhancements approach the model to the actual practice at the expense of complicating the problem further. The motivation of this study has been to explore the ability of Tabu Search to overcome these difficulties superimposed on the traditional parallel machine scheduling problem. In order to obtain a robust search mechanism, several key components of TS such as candidate list strategies, tabu classifications, tabu tenure and intensification/diversification strategies are investigated. Alternative approaches to each of these issues are developed and extensively tested on a set of problems obtained from the literature. Considerably better results are obtained and the success of the totally deterministic TS algorithm implemented is thereby demonstrated.