A GA-PSO layered encoding evolutionary approach to 0/1 knapsack optimization

Neoh, Siew Chin, Morad, Norhashimah, Lim, Chee Peng and Aziz, Zalina Abdul 2010, A GA-PSO layered encoding evolutionary approach to 0/1 knapsack optimization, International journal of innovative computing, information and control, vol. 6, no. 8, pp. 3489-3505.

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Title A GA-PSO layered encoding evolutionary approach to 0/1 knapsack optimization
Author(s) Neoh, Siew Chin
Morad, Norhashimah
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Aziz, Zalina Abdul
Journal name International journal of innovative computing, information and control
Volume number 6
Issue number 8
Start page 3489
End page 3505
Total pages 17
Publisher ICIC International
Place of publication Kumamoto, Japan
Publication date 2010-08
ISSN 1349-4198
Keyword(s) genetic algorithm
layered encoding
multi- objective
particle swarm optimization
Summary This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding structure to form a generic optimization model denoted as LGAPSO. In order to enhance the finding of both local and global optimum in the evolutionary search, the model adopts hill climbing evaluation criteria, feature of strength Pareto evolutionary approach (SPEA) as well as nondominated spread lengthen criteria. Four different sizes benchmark knapsack problems are studied using the proposed LGAPSO model. The performance of LGAPSO is compared to that of the ordinary multi-objective optimizers such as VEGA, NSGA, NPGA and SPEA. The proposed LGAPSO model is shown to be efficient in improving the search of knapsack’s optimum, capable of gaining better Pareto trade-off front.
Language eng
Field of Research 099999 Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2010, ICIC International
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048085

Document type: Journal Article
Collection: Institute for Frontier Materials
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