Study on Optimal Production Planning and Scheduling under Uncertainty by Advanced Evolutionary Algorithms

2014 Fiscal Year Final Research Report

• Project/Area Number: 24510219
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Social systems engineering/Safety system
• Research Institution: Fuzzy Logic Systems Institute
• Principal Investigator: GEN Mitsuo 一般財団法人ファジィシステム研究所, 研究部, 特別研究員 (20095003)
• Co-Investigator(Renkei-kenkyūsha): LIN Lin 財)ファジイシステム研究所, 研究部, 主任研究員 (90434331)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 進化計算法 / メータヒューリスティクス / 多目的スケジューリング / 遺伝的アルゴリズム / 分布推定アルゴリズム / 不確実環境下のスケジューリング / パネルディスプレイ / ハードディスクデバイス

Outline of Final Research Achievements

The goal of this study is to develop advanced evolutionary algorithms (AEA) for applying to practical manufacturing scheduling problems (MSP) and MSP under uncertainty environment. The results of the research project carried out as follows:
(1) Developing a multiobjective hybrid evolutionary algorithm (MoHEA): We developed a hybrid sampling strategy-based multiobjective evolutionary algorithm (HSS-MoEA) to deal with process planning and scheduling (PPS) and cooperative estimation of distribution algorithm (EDA). (2) Developing a new AEA for practical MSP: We developed adaptive HGA with fuzzy logic controller for solving hard-disc drive (HDD) manufacturing scheduling and also developed MoHGA for panel display (TFT-LCD: thin-film transistor-liquid crystal display) module assembly scheduling. (3) Developing AEA for the uncertain MSP: We developed HMoEA for assembly line balancing problem with stochastic processing time.

Free Research Field

社会システム工学・安全システム