Optimizing Multi-objective Knapsack Problem using a Hybrid Ant Colony Approach within Multi Directional Framework

Imen Ben Mansour, Imen Ben Mansour

2022

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 maintained. 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.

Paper Citation

in Harvard Style

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, pages 409-418. DOI: 10.5220/0010865600003116

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Ben Mansour I.
PY - 2022
SP - 409
EP - 418
DO - 10.5220/0010865600003116