C. Pop, V. Chifu, I. Salomie, Cristian Prigoana, Tiberiu Boros, Dorin Moldovan
{"title":"Generating Healthy Menus for Older Adults Using a Hybrid Honey Bees Mating Optimization Approach","authors":"C. Pop, V. Chifu, I. Salomie, Cristian Prigoana, Tiberiu Boros, Dorin Moldovan","doi":"10.1109/SYNASC.2015.73","DOIUrl":null,"url":null,"abstract":"This paper models the problem of generating healthy menu recommendations for older adults as an optimization problem and proposes a hybrid Honey Bees Mating Optimization method for solving this problem. The method hybridizes the state of the art Honey Bees Mating Optimization meta-heuristic by injecting strategies inspired from Genetic Algorithms, Hill Climbing, Simulated Annealing, and Tabu Search into the steps that generate new solutions of the optimization problem. The method has been integrated in a food ordering system enabling older adults to order food daily. Experiments have been conducted on several hybridization configurations to identify the most appropriate hybridization that leads to the healthy menu recommendation that best satisfies the older adult's diet recommended by the nutritionist, its culinary preferences and time and price constraints.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"98 1","pages":"452-459"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2015.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper models the problem of generating healthy menu recommendations for older adults as an optimization problem and proposes a hybrid Honey Bees Mating Optimization method for solving this problem. The method hybridizes the state of the art Honey Bees Mating Optimization meta-heuristic by injecting strategies inspired from Genetic Algorithms, Hill Climbing, Simulated Annealing, and Tabu Search into the steps that generate new solutions of the optimization problem. The method has been integrated in a food ordering system enabling older adults to order food daily. Experiments have been conducted on several hybridization configurations to identify the most appropriate hybridization that leads to the healthy menu recommendation that best satisfies the older adult's diet recommended by the nutritionist, its culinary preferences and time and price constraints.