A Menu Planning Model Using Hybrid Genetic Algorithm And Fuzzy Reasoning: A Study On Malaysian Geriatric Cancer Patients
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Date
2016-04
Authors
Ngo, Hea Choon
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
Nowadays, there are many diet recommendation models in the market that
provide general advice to the clients. However, the generated menu plan from these
models are usually very subjective and difficult to be represented systematically. Thus,
proper nutrition for the elderly is important to maintain health and well-being, which can
lead to fulfilling and independent lives. This research presents a study on ontology-based
menu planning model using hybrid genetic algorithm and fuzzy reasoning for Malaysian
geriatric cancer patients. The proposed work aims to produce a diet plan representation
based on diet plan ontology; design a planning engine by integrating genetic algorithm
with local search technique to enhance menu planning; and develop a menu planning
approach to cater for Malaysian geriatric cancer patients using fuzzy reasoning
mechanism. With the aim of planning healthy menu to patients, ontology is used to
classify nutrients, food groups, meal structure and personal profile. Following that,
hybrid genetic algorithm (HGA) is employed to ensure that the constructed menu
satisfies all the objectives and predefined constraints. Furthermore, a fuzzy logic control
(FLC) was applied in the modeling of membership functions of fuzzy sets for estimating
nutrition needs. The evidence from this study showed that HGA approach was capable to produce feasible solutions and FLC yielded significant improvements in the proposed
menu planning model.
Description
Keywords
Geriatric cancer