Bi-objective Optimization in Identical Parallel Machine Scheduling Problem

This paper presents bi-objective identical parallel machine scheduling problem with minimization of weighted sum of makespan and number of tardy jobs simultaneously. It is a known fact that identical parallel machine scheduling problem with makespan and number of tardy jobs based criteria is NP hard. Metaheuristics has become most important choice for solving NP hard problems because of their multi-solution and strong neighborhood search capabilities in a reasonable time. In this work Simulated Annealing Algorithm (SA) and Genetic Algorithm (GA) has been proposed to optimize two different objectives namely (i) minimization of make span (ii) minimization of number of tardy jobs using combined objective function (COF). The effectiveness of the proposed algorithm have been analyzed by means of benchmark problem taken from the literatures and relative performance measures for the algorithm have also been computed and analyzed. Computational results show that GA outperforms SA by a considerable margin.