Title: A co-evolutionary decomposition-based algorithm for the bi-level knapsack optimisation problem

Authors: Abir Chaabani; Lamjed Ben Said

Addresses: SMART Lab, ISG, University of Tunis, Tunisia ' SMART Lab, ISG, University of Tunis, Tunisia

Abstract: Bi-level optimisation problems (BOPs) are a class of challenging problems with two levels of optimisation tasks. These problems allow to model a large number of real-life situations in which a first decision maker, hereafter the leader, optimises his objective by taking the follower's response to his decisions explicitly into account. In this context, a new proposed algorithm called CODBA-II was suggested to solve combinatorial BOPs. The latter was able to improve the quality of generated bi-level solutions regarding to recently proposed methods. In fact, a wide range of applications fit the bi-level programming framework and real-life implementations still scarce. For this reason, we propose in this paper a co-evolutionary decomposition-based bi-level algorithm for the bi-level knapsack optimisation problem. The computational algorithm turned out to be quite efficient on both computation time and solution quality regarding to other competitive EAs.

Keywords: bi-level combinatorial optimisation; evolutionary methods; bi-level knapsack problem; BKP.

DOI: 10.1504/IJCISTUDIES.2020.1002814

International Journal of Computational Intelligence Studies, 2020 Vol.9 No.1/2, pp.52 - 67

Received: 28 Feb 2018
Accepted: 20 Sep 2018

Published online: 02 Apr 2020 *

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