A GENETIC ALGORITHM TO SOLVE THE MULTIDIMENSIONAL KNAPSACK PROBLEM

In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applications is studied and a genetic algorithm to solve the MKP is proposed. Unlike the technique of the classical genetic algorithm, initial population is not randomly generated in the proposed algorithm, thus the solution space is scanned more efficiently. Moreover, the algorithm is written in C programming language and is tested on randomly generated instances. It is seen that the algorithm yields optimal solutions for all instances.

Paper

Full text

PDF

A GENETIC ALGORITHM TO SOLVE THE MULTIDIMENSIONAL KNAPSACK PROBLEM

Semantic Scholar · Computer Science · 2013

Abstract

In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applications is studied and a genetic algorithm to solve the MKP is proposed. Unlike the technique of the classical genetic algorithm, initial population is not randomly generated in the proposed algorithm, thus the solution space is scanned more efficiently. Moreover, the algorithm is written in C programming language and is tested on randomly generated instances. It is seen that the algorithm yields optimal solutions for all instances.

References (18)

Scroll for more · 6 remaining

Similar papers

© 2026 NYSGPT2525 LLC