%0 Journal Article
%T Pareto-based Multi-criteria Evolutionary Algorithm for Parallel Machines Scheduling Problem with Sequence-dependent Setup Times
%J International Journal of Engineering
%I Materials and Energy Research Center
%Z 1025-2495
%A Shokoufi, Keyvan
%A rezaeian, Javad
%A Zarei, Mohsen
%D 2017
%\ 12/01/2017
%V 30
%N 12
%P 1863-1869
%! Pareto-based Multi-criteria Evolutionary Algorithm for Parallel Machines Scheduling Problem with Sequence-dependent Setup Times
%K multi
%K objective optimization
%K Unrelated parallel machine
%K just
%K In
%K time Scheduling
%K Controlled elitism non
%K dominated sorting genetic algorithm
%K mixed integer programming
%K Sequence
%K dependent setup time
%R
%X This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the model for real-sized applications, a Pareto-based algorithm, namely controlled elitism non-dominated sorting genetic algorithm (CENSGA), is proposed. To validate its performance, the algorithm is examined under six performance metric measures, and compared with a Pareto-based algorithm, namely NSGA-II. The results are statistically evaluated by the Mannâ€“Whitney test and t-test methods. From the obtained results based on the t-test, the proposed CENSGA significantly outperforms the NSGA-II in four out of six terms. Additionally, the statistical results from Mannâ€“Whitney test show that the performance of the proposed CENSGA is better than the NSGA- II in two out of six terms. Finally, the experimental results indicate the effectiveness of the proposed algorithm for different problems.
%U http://www.ije.ir/article_73076_0206e099bd9ad1d54af1a53028ae7e18.pdf