2009Unpublished venueRequires access

Solve Zero-One Knapsack Problem by Greedy Genetic Algorithm

Yuxiang Shao, Hongwen Xu, Weiming Yin

Open publisher page 7 citations

Abstract

In order to overcome the disadvantages of the traditional genetic algorithm and improve the speed and precision of the algorithm, the author improved the selection strategy, integrated the greedy algorithm with the genetic algorithm and formed the greedy genetic algorithm. The paper discussed the basic idea and method to solve the zero-one knapsack problem using this greedy genetic algorithm. The experiments prove the feasibility and validity of the algorithm.

About this research paper

What this paper is about

In order to overcome the disadvantages of the traditional genetic algorithm and improve the speed and precision of the algorithm, the author improved the selection strategy, integrated the greedy algorithm with the genetic algorithm and formed the greedy genetic algorithm. The paper discussed the basic idea and method to solve the zero-one knapsack problem using this greedy genetic algorithm. The experiments prove the feasibility and validity of the algorithm.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

In order to overcome the disadvantages of the traditional genetic algorithm and improve the speed and precision of the algorithm, the author improved the selection strategy, integrated the greedy algorithm with the genetic algorithm and formed the greedy genetic algorithm. The paper discussed the basic idea and method to solve the zero-one knapsack problem using this greedy genetic algorithm. The experiments prove the feasibility and validity of the algorithm.

Key concepts: Knapsack problem, Greedy algorithm, Continuous knapsack problem, Genetic algorithm, Algorithm, Greedy randomized adaptive search procedure, Mathematical optimization, Selection (genetic algorithm)

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