Solving Knapsack Problem with Genetic Algorithm Approach

Saraswat, Manish; Tripathi, Ramesh Chandra

doi:10.2139/ssrn.3565876

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Solving Knapsack Problem with Genetic Algorithm Approach

Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020

3 Pages Posted: 3 Apr 2020

See all articles by Manish Saraswat

Manish Saraswat

Geetanjali Institute of Technical Studies (GITS),

Ramesh Chandra Tripathi

TMU, Moradbad

Date Written: April 1, 2020

Abstract

The knapsack problem is preferred in analyzing area of stochastic & combinational extension with the intention of choosing objects into knapsack to avail maximum capacity while not increasing knapsack’s stowage. The main focus of this paper describes problem solving approach using genetic algorithm (GA) for the 0-1 knapsack problem. The experiments started with some initial value of Knapsack variables remain continue until getting the best value. This paper contains two sections: The first section contains concise description of the basic idea of GAs and the definition of Knapsack Problem. Second section has implementation of 0-1 Knapsack Problem using GAs.

Keywords: Genetic Algorithm, Knapsack Problem, population, Optimization, GA operators, Dynamic Programming.

Suggested Citation: Suggested Citation

Saraswat, Manish and Tripathi, Ramesh Chandra, Solving Knapsack Problem with Genetic Algorithm Approach (April 1, 2020). Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020, Available at SSRN: https://ssrn.com/abstract=3565876 or http://dx.doi.org/10.2139/ssrn.3565876