Abstract
In this paper, we present a practical case of the multiobjective knapsack problem which concerns the elaboration of the optimal action plan in the social and medico-social sector. We provide a description and a formal model of the problem as well as some preliminary computational results. We perform an empirical analysis of the behavior of three metaheuristic approaches: a fast and elitist multiobjective genetic algorithm (NSGA-II), a Pareto Local Search (PLS) algorithm and an Indicator-Based Multi-Objective Local Search (IBMOLS).
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Notes
- 1.
In social and medico-social structures, a project is defined for a period of five years. At the sixth year, the evaluation of the project is carried out and the attainment of each objective is measured. Therefore, the more there are objectives, the more the evaluation is difficult.
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Acknowledgments
We are grateful to the reviewers for their useful comments. This work was partially supported by the French Ministry for Research and Education through a CIFRE grant (number 0450/2013). We thank M. Rachid Naitali, the Director of GePI Conseil, for his support.
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Chabane, B., Basseur, M., Hao, JK. (2015). A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis. In: Dhaenens, C., Jourdan, L., Marmion, ME. (eds) Learning and Intelligent Optimization. LION 2015. Lecture Notes in Computer Science(), vol 8994. Springer, Cham. https://doi.org/10.1007/978-3-319-19084-6_23
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DOI: https://doi.org/10.1007/978-3-319-19084-6_23
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