Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem
Neural and Evolutionary Computing
2015-02-13 v1
Abstract
Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation and greedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.
Cite
@article{arxiv.1502.03699,
title = {Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem},
author = {Jun He and Yong Wang and Yuren Zhou},
journal= {arXiv preprint arXiv:1502.03699},
year = {2015}
}