Title :
Combined quantum particle swarm optimization algorithm for multi-objective nutritional diet decision making
Author_Institution :
Sch. of Comput. & Inf. Eng., Harbin Univ. of Commerce, Harbin, China
Abstract :
A assembled method based on quantum particle swarm optimization (QPSO) algorithm combined with Bayesian networks (BN) is proposed to solve complex multi-objective nutritional diet decision making problem. To realize nutritional diet decision optimization for patients, BN model for dealing with associative relationship between diseases and diets is set up to compute and update the edibility of every food in database. QPSO algorithm is selected as the core optimization algorithm to avoid being trapped in a local optimum. Actual experimental results show that such combined method is a feasible and effective approach for actual nutritional diet decision making problem.
Keywords :
belief networks; decision making; diseases; health care; medical computing; particle swarm optimisation; patient care; quantum computing; BN model; Bayesian network; QPSO algorithm; assembled method; disease prevention; healthy nutritious food edibility; multiobjective patient nutritional diet decision making; quantum particle swarm optimization algorithm; Assembly; Bayesian methods; Business; Computer networks; Costs; Decision making; Diseases; Electronic mail; Particle swarm optimization; Quantum computing; Decision Making; Multi-Objective Optimization; Nutritional Diet; Quantum Particle Swarm Optimization Algorithm;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234580