Title :
Improved hybrid adaptive genetic algorithm for solving knapsack problem
Author :
Ma, Yanqin ; Wan, Jianchen
Author_Institution :
Dept. of Coll. of Inf. Eng., Huanghe Sci. Technol. Coll., Zhengzhou, China
Abstract :
The paper solves the 0-1 knapsack problem with the hybrid adaptive genetic algorithm which combined with greedy algorithm. It presents a method for optimal design of an improved adaptive genetic algorithm and repairs the infeasible solution with greedy algorithm. Experimental results show that the new algorithm has faster convergent speed, higher robustness and more reliable stability, so this is a very attractive new approach being full of promise.
Keywords :
genetic algorithms; knapsack problems; 0-1 knapsack problem; greedy algorithm; hybrid adaptive genetic algorithm; Adaptation models; Approximation algorithms; Convergence; Genetic algorithms; Genetics; Greedy algorithms; Heuristic algorithms;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-0813-8
DOI :
10.1109/ICICIP.2011.6008329
