Mariko Tanaka
ABSTRACT
For solving multi-objective set packing problems involving constraints, this work proposes an algorithm combining an infeasible solution repair method and MOEA/D sharing the same weight vector set determining search directions in the objective space. To share the same weight vectors between repair method and evolutionary algorithm enhances the affinity of them, and the experimental results on problems with two and four objectives show that the proposed algorithm improves the search performance especially in the viewpoint of the spread of solutions in the objective space.
- M. Tanaka, Y. Yamagishi, H. Nagai, and H. Sato, "A Study on Two-Level Infeasible Solution Repair for Evolutionary Multi-objective Set Packing Optimization," In Proc. of NOLTA2017, pp. 588--591, 2017.Google Scholar
- H. Jain and K. Deb, "An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach," IEEE Trans. on EC, 18 (4), pp. 602--622, 2014.Google Scholar
Index Terms
- Infeasible solution repair and MOEA/D sharing weight vectors for solving multi-objective set packing problems
Recommendations
Adaptive Update Range of Solutions in MOEA/D for Multi and Many-Objective Optimization
SEAL 2014: Proceedings of the 10th International Conference on Simulated Evolution and Learning - Volume 8886MOEA/D, a representative multi-objective evolutionary algorithm, decomposes a multi-objective optimization problem into a number of single objective optimization problems and tries to approximate Pareto front by simultaneously optimizing each of these ...
Single-objective and multi-objective formulations of solution selection for hypervolume maximization
GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computationA new trend in evolutionary multi-objective optimization (EMO) is the handling of a multi-objective problem as an optimization problem of an indicator function. A number of approaches have been proposed under the name of indicator-based evolutionary ...
Directed mating in decomposition-based MOEA for constrained many-objective optimization
GECCO '18: Proceedings of the Genetic and Evolutionary Computation ConferenceThis work proposes a decomposition-based algorithm, CMOEA/D-DMA, for constrained many-objective optimization. For constrained multi-objective optimization, the TNSDM algorithm using the directed mating selecting infeasible solutions having better ...
Comments