NSGA-II implementation details may influence quality of solutions for the job-shop scheduling problem
Pages 1445 - 1446
Abstract
The helper-objective approach for solving the job-shop scheduling problem using multi-objective evolutionary algorithms is considered.
We implemented the approach from the Lochtefeld and Ciarallo paper using NSGA-II with the correct implementation of the non-dominated sorting procedure which is able to work with equal values of objectives. The experimental evaluation showed the significant improvement of solution quality.
We also report new best results for 16 out of 24 problem instances used in the considered paper.
References
[1]
Source code for experiments (a part of this paper). URL: https://github.com/mbuzdalov/papers/tree/master/2014-gecco-lba-jobshop.
[2]
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. A Fast Elitist Multi-Objective Genetic Algorithm: NSGA-II. Transactions on Evolutionary Computation, 6:182--197, 2000.
[3]
F.-A. Fortin, S. Grenier, and M. Parizeau. Generalizing the Improved Run-time Complexity Algorithm for Non-dominated Sorting. In Proceeding of the Fifteenth Annual Conference on Genetic and Evolutionary Computation Conference, GECCO '13, pages 615--622. ACM, 2013.
[4]
M. T. Jensen. Reducing the Run-time Complexity of Multiobjective EAs: The NSGA-II and Other Algorithms. Transactions on Evolutionary Computation, 7(5):503--515, 2003.
[5]
M. T. Jensen. Helper-Objectives: Using Multi-Objective Evolutionary Algorithms for Single-Objective Optimisation: Evolutionary Computation Combinatorial Optimization. Journal of Mathematical Modelling and Algorithms, 3(4):323--347, 2004.
[6]
D. F. Lochtefeld and F. W. Ciarallo. Helper-Objective Optimization Strategies for the Job-Shop Scheduling Problem. Applied Soft Computing, 11(6):4161--4174, 2011.
[7]
I. Petrova, A. Buzdalova, and M. Buzdalov. Improved Helper-Objective Optimization Strategy for Job-Shop Scheduling Problem. In Proceedings of the International Conference on Machine Learning and Applications, volume 2, pages 374--377. IEEE Computer Society, 2013.
Index Terms
- NSGA-II implementation details may influence quality of solutions for the job-shop scheduling problem
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July 2014
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Published: 12 July 2014
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- Government of Russian Federation
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GECCO '14
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GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%
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