A New Artificial Fish Swarm Algorithm for the Multiple Knapsack Problem

A new artificial fish swarm algorithm (AFSA) for solving the multiple knapsack problem (MKP) is introduced in this paper. In the proposed AFSA, artificial fish (AF) individuals are only allowed to search the region near constraint boundaries of the problem to be solved. For this purpose, several behaviors to be performed by AF individuals, including escaping behavior, randomly moving behavior, preying behavior and following behavior, were specially designed. Exhaustive experiments were implemented in order to investigate the proposed AFSA’s performance. The results demonstrated the proposed AFSA has the ability of finding highquality solutions with very fast speed, as compared with some other versions of AFSA based on different constraint-handling methods. This study is also meaningful for solving other constrained problems. key words: artificial fish swarm algorithm, multiple knapsack problem, constraint boundary, search region

[1]  Sancho Salcedo-Sanz,et al.  A survey of repair methods used as constraint handling techniques in evolutionary algorithms , 2009, Comput. Sci. Rev..

[2]  Qing Liu,et al.  Application of an Artificial Fish Swarm Algorithm in Symbolic Regression , 2013, IEICE Trans. Inf. Syst..

[3]  Urszula Boryczka Ants and Multiple Knapsack Problem , 2007, 6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07).

[4]  Xuan Ma,et al.  A genetic algorithm with utilizing lethal chromosomes , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[5]  Paolo Detti,et al.  A polynomial algorithm for the multiple knapsack problem with divisible item sizes , 2009, Inf. Process. Lett..

[6]  David Pisinger An exact algorithm for large multiple knapsack problems , 1999, Eur. J. Oper. Res..

[7]  Xin Yao,et al.  A Large Population Size Can Be Unhelpful in Evolutionary Algorithms a Large Population Size Can Be Unhelpful in Evolutionary Algorithms , 2022 .

[8]  A. Fukunaga Dominance in Incomplete Solvers for the Multiple Knapsack Problem , 2008 .

[9]  Carlos A. Coello Coello,et al.  Use of a self-adaptive penalty approach for engineering optimization problems , 2000 .

[10]  Ho Soo Lee,et al.  Computational Aspects of Clearing Continuous Call Double Auctions with Assignment Constraints and Indivisible Demand , 2001, Electron. Commer. Res..

[11]  Zhou Jing An optimization method of multistage stations locating in oil transportation based on fish-swarm algorithm , 2008 .

[12]  Liu Qing Artificial fish swarm algorithm for multiple knapsack problem , 2010 .

[13]  Li Xiao,et al.  An Optimizing Method Based on Autonomous Animats: Fish-swarm Algorithm , 2002 .

[14]  Yalong Zhang,et al.  Fish swarm optimization method for the two-dimensional guillotine cutting problem , 2011 .

[15]  Takeo Yamada,et al.  An exact algorithm for the fixed-charge multiple knapsack problem , 2009, Eur. J. Oper. Res..

[16]  Paolo Toth,et al.  Lower bounds and reduction procedures for the bin packing problem , 1990, Discret. Appl. Math..

[17]  Edward G. Coffman,et al.  Approximation algorithms for bin packing: a survey , 1996 .

[18]  Yao Yuxia,et al.  Global convergence proof of artificial fish swarm algorithm for solving combinatorial optimization problems , 2012 .

[19]  Anthony Chen,et al.  Constraint handling in genetic algorithms using a gradient-based repair method , 2006, Comput. Oper. Res..

[20]  Ana Maria A. C. Rocha,et al.  Fish swarm intelligent algorithm for bound constrained global optimization , 2009 .

[21]  Hsing-Chih Tsai,et al.  Modification of the fish swarm algorithm with particle swarm optimization formulation and communication behavior , 2011, Appl. Soft Comput..

[22]  Gilbert Laporte,et al.  Upper bounds and algorithms for the maximum cardinality bin packing problem , 2003, Eur. J. Oper. Res..

[23]  S. Martello,et al.  Heuristische Algorithmen zur Packung von mehreren Rucksäcken , 1981 .

[24]  Paolo Toth,et al.  Heuristic algorithms for the multiple knapsack problem , 1981, Computing.

[25]  Wen-Hong Wu,et al.  The second generation of self-organizing adaptive penalty strategy for constrained genetic search , 2004 .

[26]  Song Hai-zhou Hybrid genetic algorithm for multi-knapsack problem , 2009 .

[27]  Qing Liu,et al.  An artificial fish swarm algorithm for steiner tree problem , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[28]  Qing Liu,et al.  Artificial fish swarm algorithm for multiple knapsack problem: Artificial fish swarm algorithm for multiple knapsack problem , 2010 .

[29]  Nicos Christofides,et al.  The Loading Problem , 1971 .