Review Article: Solving 0-1 knapsack problem by a novel global harmony search algorithm
Applied Soft Computing
Novel binary encoding differential evolution algorithm
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Wisdom of artificial crowds algorithm for solving NP-hard problems
International Journal of Bio-Inspired Computation
Hybrid differential evolution for knapsack problem
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Chemical reaction optimization with greedy strategy for the 0-1 knapsack problem
Applied Soft Computing
Solving 0-1 knapsack problem by continuous ACO algorithm
International Journal of Computational Intelligence Studies
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A Schema-Guiding Evolutionary Algorithm (SGEA) is proposed in this paper. The novel SGEA has many good features. It proposes the schema-modified operator to adjust the distribution of the population. What's more, it constructs an elite-schema space and proposes the cluster-center schema to guide the direction of individual's evolution. And by such two strategies, the diversity of the population and the local and global search power can be greatly improved. The experimental results show that the SGEA proposed in this paper has many better performances, compared with other methods such as simple genetic algorithm, greedy algorithm and so forth.