Multi-objective Optimization with weighted User Preferences in Meal Planning System

Abstract

Food waste and food loss is becoming a big social problem in the world. The main reason of throwing away food before being eaten is best-before date expiration. This paper presents a content-based recommender system for meal planning that aims to reduce the amount of expired food in a family. Moreover, such a recommender system is required to not only extract user's preferences but also suggest well-balanced diet. The recommender system therefore has the multi-objective functions to minimize the amount of expired food and adjust caloric intake. Furthermore, we applied a multi-island genetic algorithm to the recommender system and used weighting factors to each objective that users can adjust according to their preference.