Minimizing Multiple Objective Function for Scheduling Machine Problems

Abstract

The multi-criteria problem of scheduling n jobs on a single machine was considered in this paper. The criteria belong to minimize total completion times, total tardiness and total late work and minimize total completion times, total tardiness and maximum late work by using some exact and local search methods. The proposed methods for solving these minimization problems were seemed to be helpful in finding the set of all efficient solutions. This set of all efficient solutions is not easy to find, therefore, it could be preferable to have an approximation to that set in a reasonable amount of time. Therefore branch and bound (BAB) technique was proposed as an exact approach, while the Genetic algorithm (GA) and Particle Swarm Optimization (PSO) methods were also proposed as local search methods.

Keywords: Multiple objective Scheduling, Branch and Bound, Pareto Optimal Solutions, Genetic Algorithm, Particle Swarm Optimization.