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计算机应用研究 2011
Novel multi-objective particle swarm optimization algorithm for solving human resource allocation problem
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Abstract:
This paper proposed a novel multi-objective particle swarm optimization algorithm for solving the human resource allocation problem. It ensured that the individual equably dispersing in the feasible solution space by using the population quadrature initialization,effectively retained approximation Pareto off-the-press non-inferior solution by using external archive non-inferior solution delete selected strategy based on the grid technology, and promoted the probability of particles convergence to the Pareto frontier by introducting a generalized learning strategies. Results of the numerical experiment show that the proposed algorithm is effective and useful in solving the human resource allocation problem, and has good application value.