A tabu search algorithm for the open shop scheduling problem

Abstract

An approximation algorithm of finding a minimum makespan in a nonpreemptive open shop is presented. The algorithm is based on the tabu search technique with a neighborhood structure defined using blocks of operations on a critical path. An efficient procedure is also developed for evaluating a neighborhood. The algorithm is tested on 450 randomly generated problems and a set of 60 benchmarks. Computational results show that the algorithm finds extremely high-quality solutions for all of the test problems in a reasonable amount of computation time, and hence demonstrate the potential of the algorithm to efficiently schedule open shops. Scope and purpose Shop scheduling problems like flow shop problems, job shop problems and open shop problems, which are widely used for modeling industrial production processes, have been receiving increasing attention from researchers. Most of the published results in this area have been focused on flow shop or job shop scheduling problems. This paper addresses the problem of scheduling open shops. An efficient local search algorithm based on the tabu search technique is proposed for solving the open shop scheduling problem with the objective of minimizing makespan. Computational results show that the algorithm performs extremely well on both benchmarks and randomly generated problems.