A modified shuffled frog leaping algorithm with genetic mutation for combinatorial optimization

Authors:
Kaushik Kumar Bhattacharjee;Sarada Prasad Sarmah
Affiliations:
Deptt. of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur, India;Deptt. of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur, India
Venue:
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
Year:
2012

Citing 6
Cited 0

A Genetic Algorithm for the Multidimensional Knapsack Problem

Journal of Heuristics
Adaptive memory search for multidemand multidimensional knapsack problems

Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Heuristic approaches for the two- and three-dimensional knapsack packing problem

Computers and Operations Research
Comparison among five evolutionary-based optimization algorithms

Advanced Engineering Informatics
An ant colony optimization approach for the multidimensional knapsack problem

Journal of Heuristics
A variable-grouping based genetic algorithm for large-scale integer programming

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work, we propose modified versions of shuffled frog leaping algorithm (SFLA) to solve multiple knapsack problems (MKP). The proposed algorithm includes two important operations: repair operator and genetic mutation with a small probability. The former is utilizing the pseudo-utility to repair infeasible solutions, and the later can effectively prevent the algorithm from trapping into the local optimal solution. Computational experiments with a large set of instances show that the proposed algorithm can be an efficient alternative for solving 0/1 multidimensional knapsack problem.