Approach of Fuzzy Theory and Hill Climbing Based Recommender for Schedule of Life
Nobuki Saito, Tetsuya Oda, Yuki Nagai, Kazuho Kanahara, Masaharu Hirota, Kengo Katayama
Abstract
For maintaining good health, it is important to take meals and exercises regularly. However, it has been reported that the number of jobs with irregular work times is increasing. In addition, determining meal and exercise times to maintain health during irregular work times is an NP-hard problem because it needs to resolve the multi-objective optimization. In this paper, we propose a recommender system based on fuzzy theory and hill climbing approach that presents a schedule of meals and exercises in a daily life including irregular work time. We show the simulation results and case study using the proposed system.
Topics & Concepts
ScheduleRecommender systemComputer scienceClimbingFuzzy logicHill climbingWork (physics)Artificial intelligenceWork scheduleMachine learningOperations researchIndustrial engineeringMathematical optimizationScheduling (production processes)MathematicsEngineeringOperating systemStructural engineeringMechanical engineeringIntuitionistic Fuzzy Systems ApplicationsSleep and Work-Related Fatigue