评价函数和排序遗传算法在多模式连续膳食计划中的有效性

T. Kashima, Hiroshi Someya, Y. Orito
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引用次数: 1

摘要

连续膳食计划是一个组合优化问题,它确定了由连续几天组成的长时间内的膳食计划。一顿饭有不同的特点,比如食物风格、食材和烹饪方法。针对这一问题,本文提出了一种基于移动区间信息熵的评价函数。功能衡量餐点特征在平面上的呈现顺序。此外,我们设计了一种特定基因型的置换遗传算法,并将其应用于该问题。在数值实验中,我们证明了使用我们的函数的连续用餐计划可以看作是一个多模态问题,然后证明了我们的排列遗传算法得到的用餐计划是一个很好的解决方案,其中膳食特征的外观顺序变化很大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effectiveness of evaluation function and permutation GA in multimodal consecutive meals planning
The consecutive meals planning is a combinatorial optimization problem that determines a meals plan on a long period consisting of consecutive days. A meal is characterized in different characteristics such as food style, ingredient, and cooking method. For the problem, this paper proposes an evaluation function using information entropies on moving intervals. The function measures the appearance order of meal's characteristics on the plan. In addition, we design a specific genotype of a permutation GA and apply it to this problem. In the numerical experiments, we show that the consecutive meals planning employing our function can be viewed as a multimodal problem and then show that our meals plan obtained by the permutation GA is a good solution with large variation of appearance order of meal's characteristics.
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