A multi-criteria approach for nurse scheduling fuzzy simulated metamorphosis algorithm approach

M. Mutingi, C. Mbohwa
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引用次数: 10

Abstract

Motivated by the biological metamorphosis process and the need to solve multi-objective optimization problems with conflicting and fuzzy goals and constraints, this paper proposes a simulated metamorphosis algorithm, based on the concepts of biological evolution in insects, such as moths, butterflies, and beetles. By mimicking the hormone controlled evolution process the algorithm works on a single candidate solution, going through initialization, iterative growth loop, and finally maturation loop. The method is a practical way to optimizing multi-objective problems with fuzzy conflicting goals and constraints. The approach is applied to the nurse scheduling problem. Equipped with the facility to incorporate the user's choices and wishes, the algorithm offers an interactive approach that can accommodate the decision maker's expert intuition and experience, which is otherwise impossible with other optimization algorithms. By using hormonal guidance and unique operators, the algorithm works on a single candidate solution, and efficiently evolves it to a near-optimal solution. Computational experiments show that the algorithm is competitive.
一种多准则的护士调度模糊模拟变态算法方法
基于生物变态过程以及解决目标和约束相互冲突和模糊的多目标优化问题的需要,本文提出了一种基于飞蛾、蝴蝶、甲虫等昆虫生物进化概念的模拟变态算法。通过模拟激素控制的进化过程,该算法在单个候选解上工作,经历初始化,迭代生长循环,最后成熟循环。该方法是求解具有模糊目标冲突和约束的多目标优化问题的一种实用方法。将该方法应用于护士调度问题。该算法具备整合用户选择和愿望的功能,提供了一种交互式方法,可以适应决策者的专家直觉和经验,这是其他优化算法无法做到的。该算法通过使用激素引导和唯一算子,从单个候选解出发,并有效地进化到接近最优解。计算实验表明,该算法具有一定的竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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