A simple improvement heuristic for attributed grammatical evolution with lookahead to solve the multiple knapsack problem

Authors:
Muhammad Rezaul Karim;Conor Ryan
Affiliations:
Biocomputing and Developmental Systems Group, Department of Computer Science and Information Systems, University of Limerick, Ireland;Biocomputing and Developmental Systems Group, Department of Computer Science and Information Systems, University of Limerick, Ireland
Venue:
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Year:
2011

Citing 6
Cited 0

Algorithms for constraint-satisfaction problems: a survey

AI Magazine
The zero/one multiple knapsack problem and genetic algorithms

SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Grammatical Evolution: Evolving Programs for an Arbitrary Language

EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Compilers: Principles, Techniques, and Tools (2nd Edition)

Compilers: Principles, Techniques, and Tools (2nd Edition)
ExGA II: an improved exonic genetic algorithm for the multiple knapsack problem

Proceedings of the 9th annual conference on Genetic and evolutionary computation
A new approach to solving 0-1 multiconstraint knapsack problems using attribute grammar with lookahead

EuroGP'11 Proceedings of the 14th European conference on Genetic programming

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we introduce a simple improvement heuristic to be used with Attribute Grammar with Lookahead approach (AG+LA), a recently proposed mapping approach for Grammatical Evolution (GE) using an attribute grammar (AG) to solve the Multiple Knapsack Problem (MKP). The results presented in this paper show that the proposed improvement heuristic can improve the quality of solutions obtained by AG+LA with little computational effort.