Title: A discrete binary version of bat algorithm for multidimensional knapsack problem

Authors: Sara Sabba; Salim Chikhi

Addresses: MISC Laboratory, Computer Science Department, Faculty of Engineering Sciences, Constantine University 2, Route Ain El Bey, Constantine 25017, Algeria ' MISC Laboratory, Computer Science Department, Faculty of Engineering Sciences, Constantine University 2, Route Ain El Bey, Constantine 25017, Algeria

Abstract: The nature has become a main inspiration source of scientists for developing new intelligent systems and techniques. Nature-inspired meta-heuristics is a kind of algorithms that imitate the social behaviour of some biological species. The bat algorithm (BA) is a new bio-inspired algorithm recently introduced by Yang (2010a). It is an optimisation method that is based on the echolocation behaviour of microbats. Firstly, the BA has been proposed for continuous problems. In this paper, we propose a discrete binary bat algorithm (BinBA) for solving the optimisation problems in binary space. The proposed algorithm is based on the sigmoid function used by Kennedy and Eberhart in 1997 for their binary particle swarm optimisation algorithm. The BinBA was tested on hard instances of the multidimensional knapsack problem. The obtained results are very promising compared to other bio-inspired algorithms.

Keywords: discrete optimisation; bio-inspired computation; binary bat algorithm; multidimensional knapsack problem; MKP; sigmoid function.

DOI: 10.1504/IJBIC.2014.060598

International Journal of Bio-Inspired Computation, 2014 Vol.6 No.2, pp.140 - 152

Received: 23 Feb 2013
Accepted: 06 Oct 2013
Published online: 27 Sep 2014 *

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