A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem

TL;DR

This paper introduces a revised weight-coded evolutionary algorithm with a new decoding method and heuristic initialization, demonstrating superior performance on multidimensional knapsack problems compared to previous algorithms and benchmarks.

Contribution

The paper presents a novel revised weight-coded evolutionary algorithm with improved decoding and initialization techniques for solving multidimensional knapsack problems.

Findings

Outperforms previous weight-coded evolutionary algorithms

Achieves better results than existing benchmarks and OR-library solutions

Demonstrates effectiveness on multidimensional knapsack problem instances

Abstract

A revised weight-coded evolutionary algorithm (RWCEA) is proposed for solving multidimensional knapsack problems. This RWCEA uses a new decoding method and incorporates a heuristic method in initialization. Computational results show that the RWCEA performs better than a weight-coded evolutionary algorithm proposed by Raidl (1999) and to some existing benchmarks, it can yield better results than the ones reported in the OR-library.