Authors: Hao Li; Peng Bai; Hu-Sheng Wu
Addresses: Equipment Development and Application Research Center, Air Force Engineering University, Xi'an, China; Department of Intelligence, Air Force Early Warning Academy, Wuhan, China ' Equipment Development and Application Research Center, Air Force Engineering University, Xi'an, China ' Materiel Engineering College, Armed Police Force Engineering University, Xi'an, China
Abstract: Wolf Pack Algorithm (WPA) has been successfully applied in unconstrained global optimisation problems. In order to effectively solve the multi-constrained combinatorial optimisation problem such as Multidimensional Knapsack Problem (MKP), a hybrid repair operator based on its specific knowledge is designed to repair and improve the infeasible solutions. Moreover, inspired by the reproductive modes of wolf pack, with the help of binary code, a Hybrid Binary Wolf Pack Algorithm (HBWPA) is proposed. Then HBWPA was tested on problems from the OR-Library to validate and demonstrate the efficiency of the proposed algorithm. The results were compared with those obtained by other two start-of-the-art existing algorithms, modified binary particle swarm optimisation and chaotic binary swarm optimisation with time-varying acceleration coefficients. Experimental results show that the proposed algorithm not only found comparable solutions for the standard MKP of different size, but also has good computational robustness.
Keywords: combinatorial optimisation; evolutionary computation; wolf pack algorithm; multidimensional knapsack problem.
International Journal of Wireless and Mobile Computing, 2017 Vol.12 No.3, pp.291 - 304
Received: 23 Jun 2016
Accepted: 22 Dec 2016
Published online: 27 Jun 2017 *