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The 0-1 knapsack problem is a well-known combinatorial optimisation problem.Approximation algorithms have been designed for solving it and they returnprovably good solutions within polynomial time. On the other hand, geneticalgorithms are well suited for solving the knapsack problem and they findreasonably good solutions quickly. A naturally arising question is whethergenetic algorithms are able to find solutions as good as approximationalgorithms do. This paper presents a novel multi-objective optimisation geneticalgorithm for solving the 0-1 knapsack problem. Experiment results show thatthe new algorithm outperforms its rivals, the greedy algorithm, mixed strategygenetic algorithm, and greedy algorithm + mixed strategy genetic algorithm.

A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem