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Authors: Imen Ben Mansour 1 ; 2

Affiliations: 1 ENSI-LARIA, University of Manouba, Tunisia ; 2 ESPRIT School of Engineering, Tunis, Tunisia

Keyword(s): Knapsack Problem, Multi-objective Optimization, Ant Colony Optimization, Local Search Method, Multi-directional Framework.

Abstract: Balancing the convergence and diversity simultaneously is very challenging for multi-objective evolutionary algorithms on solving multi-objective optimization problems (MOPs). The proposed approach MD-HACO coupled an Ant Colony Optimization (ACO) algorithm with a multi-objective local search procedure, and evolves it into a multi-directional framework. The idea is to optimize the overall quality of Pareto set approximation by using different configurations of the hybrid approach by means of different directional vectors. During the optimization process, the artificial ants work in different search directions in the objective space trying to approximate small parts of the Pareto front. Afterward, a local search procedure is applied to each sub-region to enhance the search process toward the extreme Pareto-optimal solutions with respect to the weight vector under consideration. A multi-directional set holding the non-dominated solutions according to all directional archives is maintain ed. The proposed approach is tested on widely used multi-objective multi-dimensional knapsack problem (MOMKP) instances and compared with well-known state-of-the-art algorithms. Experiments highlight that the use of a multi-directional paradigm as well as a hybrid schema can lead to interesting results on the MOMKP and ensure a good balance between convergence and diversity. (More)

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Paper citation in several formats:
Ben Mansour, I. (2022). Optimizing Multi-objective Knapsack Problem using a Hybrid Ant Colony Approach within Multi Directional Framework. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 409-418. DOI: 10.5220/0010865600003116

@conference{icaart22,
author={Imen {Ben Mansour}.},
title={Optimizing Multi-objective Knapsack Problem using a Hybrid Ant Colony Approach within Multi Directional Framework},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2022},
pages={409-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010865600003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Optimizing Multi-objective Knapsack Problem using a Hybrid Ant Colony Approach within Multi Directional Framework
SN - 978-989-758-547-0
IS - 2184-433X
AU - Ben Mansour, I.
PY - 2022
SP - 409
EP - 418
DO - 10.5220/0010865600003116
PB - SciTePress