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2010•Journal of Heilongjiang Institute of TechnologyRequires access

The solution to knapsack problem with genetic greedy algorithm

Dan Guo

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Abstract

Knapsack problem is solved by the hybrid genetic and greedy algorithm.We proposed a method that is used to solve premature convergence with operator compensation.The method is able to overcome premature convergence of genetic algorithms.A deterministic strategy is added to the crossover operation and a non-deterministic strategy is added to the mutation operation in the algorithm so that the algorithm has better convergence performance.The experimental results show the better performance of the improved algorithm for solving knapsack problem.

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What this paper is about

Knapsack problem is solved by the hybrid genetic and greedy algorithm.We proposed a method that is used to solve premature convergence with operator compensation.The method is able to overcome premature convergence of genetic algorithms.A deterministic strategy is added to the crossover operation and a non-deterministic strategy is added to the mutation operation in the algorithm so that the algorithm has better convergence performance.The experimental results show the better performance of the improved algorithm for solving knapsack problem.

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Available abstract

Knapsack problem is solved by the hybrid genetic and greedy algorithm.We proposed a method that is used to solve premature convergence with operator compensation.The method is able to overcome premature convergence of genetic algorithms.A deterministic strategy is added to the crossover operation and a non-deterministic strategy is added to the mutation operation in the algorithm so that the algorithm has better convergence performance.The experimental results show the better performance of the improved algorithm for solving knapsack problem.

Key concepts: Knapsack problem, Crossover, Continuous knapsack problem, Mathematical optimization, Greedy algorithm, Convergence (economics), Premature convergence, Genetic algorithm

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