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2015 | OriginalPaper | Chapter

A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis

Authors : Brahim Chabane, Matthieu Basseur, Jin-Kao Hao

Published in: Learning and Intelligent Optimization

Publisher: Springer International Publishing

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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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previous chapter Generating Training Data for Learning Linear Composite Dispatching Rules for Scheduling
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Footnotes
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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Metadata
Title
A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis
Authors
Brahim Chabane
Matthieu Basseur
Jin-Kao Hao
Copyright Year
2015
Book
Learning and Intelligent Optimization

Print ISBN: 978-3-319-19083-9

Electronic ISBN: 978-3-319-19084-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-19084-6_23

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