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Authors: Imen Ben Mansour ; Ines Alaya and Moncef Tagina

Affiliation: National School of Computer Sciences, COSMOS Laboratory and University of Manouba, Tunisia

ISBN: 978-989-758-262-2

Keyword(s): Multi-objective Multidimensional Knapsack Problem, Iterated Local Search, Scalarization Functions, Tchebycheff Functions.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Enterprise Software Technologies ; Health Engineering and Technology Applications ; Intelligent Problem Solving ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Software Engineering ; Symbolic Systems

Abstract: The multi-objective multidimensional knapsack problem (MOMKP) which is one of the hardest multi-objective combinatorial optimization problems, presents a formal model for many real world problems. Its main goal consists in selecting a subset of items in order to maximize m objective functions with respect to q resource constraints. For that purpose, we present in this paper a resolution approach based on a Min-Max Tchebycheff iterated Local Search algorithm called Min-Max TLS. In this approach, we propose designing a neighborhood structure employing a permutation process to exploit the most promising regions of the search space while considering the diversity of the population. Therefore, Min-Max TLS uses Min-Max N(s) as a neighborhood structure, combining a Min-Extraction-Item algorithm and a Max-Insertion-Item algorithm. Moreover, in Min-Max TLS two Tchebycheff functions, used as a selection process, are studied: the weighted Tchebycheff (WT) and the augmented weighted Tchebycheff ( AugWT). Experimental results are carried out with nine well-known benchmark instances of MOMKP. Results have shown the efficiency of the proposed approach in comparison to other approaches. (More)

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Paper citation in several formats:
Ben Mansour, I.; Alaya, I. and Tagina, M. (2017). A Min-Max Tchebycheff Based Local Search Approach for MOMKP.In Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-262-2, pages 140-150. DOI: 10.5220/0006433801400150

@conference{icsoft17,
author={Imen Ben Mansour. and Ines Alaya. and Moncef Tagina.},
title={A Min-Max Tchebycheff Based Local Search Approach for MOMKP},
booktitle={Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2017},
pages={140-150},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006433801400150},
isbn={978-989-758-262-2},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - A Min-Max Tchebycheff Based Local Search Approach for MOMKP
SN - 978-989-758-262-2
AU - Ben Mansour, I.
AU - Alaya, I.
AU - Tagina, M.
PY - 2017
SP - 140
EP - 150
DO - 10.5220/0006433801400150

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