Hybridizing Harmony Search Algorithm with Multi-Parent Crossover to Solve Real World Optimization Problems

Iyad Abu Doush, Faisal Alkhateeb, Eslam Al Maghayreh, Mohammed Azmi Al-Betar and Basima Hani F. Hasan
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Iyad Abu Doush: Computer Science Department, Yarmouk University, Irbid, Jordan
Faisal Alkhateeb: Computer Science Department, Yarmouk University, Irbid, Jordan
Eslam Al Maghayreh: Computer Science Department, Yarmouk University, Irbid, Jordan
Mohammed Azmi Al-Betar: Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Irbid, Jordan
Basima Hani F. Hasan: Computer Science Department, Yarmouk University, Irbid, Jordan

International Journal of Applied Metaheuristic Computing (IJAMC), 2013, vol. 4, issue 3, 1-14

Abstract: Harmony search algorithm (HSA) is a recent evolutionary algorithm used to solve several optimization problems. The algorithm mimics the improvisation behaviour of a group of musicians to find a good harmony. Several variations of HSA have been proposed to enhance its performance. In this paper, a new variation of HSA that uses multi-parent crossover is proposed (HSA-MPC). In this technique three harmonies are used to generate three new harmonies that will replace the worst three solution vectors in the harmony memory (HM). The algorithm has been applied to solve a set of eight real world numerical optimization problems (1-8) introduced for IEEE-CEC2011 evolutionary algorithm competition. The experimental results of the proposed algorithm are compared with the original HSA, and two variations of HSA: global best HSA and tournament HSA. The HSA-MPC almost always shows superiority on all test problems.

Date: 2013
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