专家分配问题的自适应并行遗传算法

Junqing Li, Juping Peng, Ying Wei
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引用次数: 3

摘要

同行评议作为一种评价方法,被广泛应用于许多商业领域。任命的专家的素质将影响到最后评价的结果,因为专家的专业知识将对评价产生直接影响。本文首先分析了专家分配问题,然后研究了专家分配问题的数学模型和如何获得最优Pareto,最后讨论了应用遗传算法解决专家分配问题的可行性。主要讨论了在专家分配过程中如何求解APGA,并给出了该问题的APGA求解过程。实验证明,该算法能有效地解决专家分配问题。同时,与随机搜索算法和遗传算法(SGA)分配结果相比,APGA在收敛速度和搜索能力上都有明显的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Parallel Genetic Algorithm for Expert Assignment Problem
As an evaluation method, peer review is used in many business fields. The quality of experts appointed will affect the results of the final evaluation since experts' expertise will have a direct impact on evaluation. This paper first analyzes the problem of expert assignment, then researches on its mathematical model and how to get the optimal Pareto, and finally discusses the feasibility of solving the problem of expert assignment through the application of genetic algorithms. It mainly discusses how to solve APGA in the expert assignment process, and then gives out the process of APGA solution to the problem. The test proved that the APGA can effectively solve expert assignment problem. The same time, and random search algorithm and genetic algorithm (SGA) to assign the results of APGA in the convergence speed and search ability has obvious advantages.
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