Title :
The Modified Hybrid Adaptive genetic algorithm for 0–1 knapsack problem
Author_Institution :
Sch. of Inf. & Eng., Huanghe Sci. Technol. Coll., Zhengzhou, China
Abstract :
The paper solves the 0-1 knapsack problem with the modified adaptive genetic transform algorithm which combined with greedy transform algorithm. By means of mixing adaptive crossover and mutation with diversity-guided mutation and modifying adaptive crossover strategies, an adaptive genetic algorithm with diversity-guided mutation was developed and repaired the infeasible solution with greedy transform algorithm. New algorithm will converge to the global optimum and do not lead to premature convergence. Experimental results show that the new algorithm has faster convergent speed, higher robustness and more reliable stability, and it is very effective for 0-1 knapsack problem.
Keywords :
combinatorial mathematics; genetic algorithms; greedy algorithms; knapsack problems; transforms; 0-1 knapsack problem; adaptive crossover strategies; adaptive mutation; combinatorial optimization; diversity-guided mutation; greedy transform algorithm; modified hybrid adaptive genetic algorithm; Approximation algorithms; Convergence; Genetic algorithms; Genetics; Heuristic algorithms; Probability; Transforms; Adaptive Genetic Algorithm; Diversity-guided Mutation; Global Optimum; Greedy Transform Algorithm; Premature Convergence;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244047