Research Review: A Study on Ontology-based and Hybrid Genetic Algorithms Approach in Menu Planning Model for Malaysian Old Folks Home

 

Research Review: A Study on Ontology-based and Hybrid Genetic Algorithms Approach in Menu Planning Model for Malaysian Old Folks Home
2014-10-23
1500 until 1630
Meeting Room 7th Floor
Ngo Hea Choon
Assoc. Prof. Dr. Cheah Yu-N
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The number of elderly in Malaysia is not only rising rapidly but also in their life expectancies. Increasing number of old age group presents a real challenge to nutritionists and health professionals. Thus, proper nutrition for the elderly is important to maintain the health and well-being of older people that can leads fulfilling and independent lives. This research presents a study on menu planning using ontology-based and hybrid genetic algorithms approach for Malaysian old folks home in general and cancer disease in particular. Nowadays, there are many diet recommendation systems in the market that provide general advice to the clients. These systems are still insufficient to provide customized diet plan based on the older people who might be at risk of malnutrition. We are attempted to consider elderly with certain chronic disease such as cancer, diabetes, chronic kidney disease, hypertension and hyperlipidemia. In this work, we take into account the elderly with cancer disease to support their nutrition plan. In the aims to discover diets and food products that deliver health to elderly, ontology is used to classify nutrients, food groups and meal structure. Following that, Hybrid genetic algorithms are employed to ensure that the constructed menu is satisfied all the objectives and predefined constraints. Instead of Boolean logic, a fuzzy logic control system was applied in modeling of membership functions of fuzzy sets for estimating nutrition needs in elderly with cancer disease. Fuzzy membership functions are constructed to describe the range of nutrients intake in the range from deficient to excess amounts. It is important to guide dietitians towards a standardized dietary management along the nutrition care process for cancer patients in order to improve patients’ outcome. The proposed work aims to (i) produce a diet plan representation based on diet plan ontology; (ii) design a planning engine by integrating genetic algorithms with local search technique to enhance menu plan; (iii) develop a special menu plan to cater patients with cancer disease using fuzzy reasoning mechanism. The evidence from this study showed that the proposed methods yield significant improvement in menu planning model.
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