Title :
Fuzzy-MOGA and Production Planning Optimization
Author :
Hong-wei, Zhang ; Zhe-yu, Shen ; Yong, Lin ; Hong-ping, Shu
Author_Institution :
Dept. of Comput., Chengdu Univ. of Inf. Technol., Chengdu, China
Abstract :
The fuzzy rule-based genetic algorithm (fuzzy-MOGA) is proposed in the paper to solve the problem of multi-objective optimization. The original chromosomes are generated with heuristic information. The Pareto optimal solutions are built by the arena´s principle on the partial order set, so that it is easy to search the non-convex solution and it dos not need to determine weight value any more, which encountered by the aggregation function approach. Fuzzy-MOGA is used to solve the production plan optimization in SCM. Because the fuzzy-rule for production distribution facilitates can easy express explicit knowledge, the limitation of greedy algorithm can be avoided. Therefore, it not only displays evidently efficiency of the algorithm and but also can find the complete Pareto front.
Keywords :
Pareto optimisation; fuzzy set theory; genetic algorithms; production planning; supply chain management; Pareto optimal solution; SCM; aggregation function approach; fuzzy rule; genetic algorithm; greedy algorithm; multiobjective optimization problem; production distribution; production planning optimization; supply chain management; Biological cells; Costs; Displays; Genetic algorithms; Greedy algorithms; Information technology; Manufacturing; Optimized production technology; Production planning; Transportation; AP; GA; Pareto optimal solution; Pruefer number; fuzzy rule; multi-objective optimization; production planning;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.547
