Choice Function-based Constructive Hyper-Heuristic for Generating Personalized Healthy Menu Recommendations

V. Chifu, C. Pop, Adrian Birladeanu, Nicolae Dragoi, I. Salomie
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引用次数: 3

Abstract

This paper presents a Choice Function-based Constructive Hyper-Heuristic for generating personalized healthy menu recommendations based on a person’s nutrition, price and delivery time constraints. We model the problem of generating personalized healthy menus as an optimization problem for which the search space consists of a set of food packages, the solution is represented as a menu containing five food packages for each meal of the day, and the fitness function evaluates the degree to which a menu personalizes a person’s profile. In each step of the proposed hyper-heuristic’s iterative phase, a low level domain independent heuristic is chosen to be applied on the current menu, based on its affinity and competence. The hyper-heuristic has been evaluated on a set of persons’ profiles and a set of food packages developed in-house.
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基于选择函数的生成个性化健康菜单推荐的建设性超启发式算法
本文提出了一种基于选择函数的建设性超启发式算法,用于根据个人的营养、价格和配送时间约束生成个性化的健康菜单推荐。我们将生成个性化健康菜单的问题建模为一个优化问题,其中搜索空间由一组食品包装组成,解决方案表示为包含每天每餐五种食品包装的菜单,并且适应度函数评估菜单个性化个人资料的程度。在提出的超启发式迭代阶段的每个步骤中,根据其亲和度和能力选择一个低层次域独立启发式应用于当前菜单。超启发式已经评估了一组人的简介和一套内部开发的食品包装。
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