DocumentCode :
1919291
Title :
A new ant colony optimization for the knapsack problem
Author :
Zhao, Peiyi ; Zhao, Peixin ; Zhang, Xin
fYear :
2006
fDate :
17-19 Nov. 2006
Firstpage :
1
Lastpage :
3
Abstract :
The knapsack problem is one of the classical NP-hard problems in operations research. It has been thoroughly studied in the last few decades and several exact algorithms for its solution can be found in the literature. In this paper, we propose a new ant colony optimization (ACO) algorithm for solving the knapsack problem. Comparing with the basic ACO, this improved algorithm combines inner mutation and outer mutation that make it more effective and efficient in solving the knapsack problem. Numerical example is presented to illustrate the model
Keywords :
knapsack problems; optimisation; NP-hard problem; ant colony optimization algorithm; knapsack problem; operations research; Ant colony optimization; Biological system modeling; Computer science; Educational institutions; Genetic mutations; NP-hard problem; Operations research; Particle swarm optimization; Polynomials; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Industrial Design and Conceptual Design, 2006. CAIDCD '06. 7th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
1-4244-0683-8
Electronic_ISBN :
1-4244-0684-6
Type :
conf
DOI :
10.1109/CAIDCD.2006.329439
Filename :
4127097
Link To Document :
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