Article ID Journal Published Year Pages File Type
6422779 Journal of Computational and Applied Mathematics 2014 8 Pages PDF
Abstract
This paper proposes a simplified binary version of the artificial fish swarm algorithm (S-bAFSA) for solving 0-1 quadratic knapsack problems. This is a combinatorial optimization problem, which arises in many fields of optimization. In S-bAFSA, trial points are created by using crossover and mutation. In order to make the points feasible, a random heuristic drop_item procedure is used. The heuristic add_item is also implemented to improve the quality of the solutions, and a cyclic reinitialization of the population is carried out to avoid convergence to non-optimal solutions. To enhance the accuracy of the solution, a swap move heuristic search is applied on a predefined number of points. The method is tested on a set of benchmark 0-1 knapsack problems.
Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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