題目：Hybrid Multiobjective Evolutionary Algorithms: Case Study of Panel Devices Manufacturing Scheduling

時(shí)間：2018年10月26日（周五）下午：14:00-16:00

地點(diǎn)：bwin必贏唯一官網(wǎng)315會議室

主講人：Prof. Mitsuo Gen（玄光男教授）

Abstract:

Many combinatorial optimization problems(COPs) in the real-world manufacturing systems impose on more complex issues,such as complex structure, nonlinear constraints, and multiple objectives to behandled simultaneously and make the problem intractable to the traditionalapproaches because of NP-hard combinatorial problems. In order to develop anefficient solution algorithm that is in a sense "best solution" thatis, whose reasonable computational time for NP-hard COPs met in practice, wehave to consider the following very important issues: 1) Quality of solution;2) Computational time and effectiveness of the nondominated solutions formultiobjective optimization problem (MOP). Evolutionary Algorithms (EAs) hasattracted significantly attention with respect to complexity schedulingproblems, which is referred to evolutionary scheduling. However, EAs differ inthe implementation details and the nature of the particular scheduling problemapplied. In order to have an effective implementation of EAs for a scheduling,this talk focuses on making a survey of case study based on hybrid andmultiobjective EAs. Starting from scheduling description, we identify theclassification and scheduling problems. Then we present the hybridizationtechniques to enhancing EAs. Finally, we also present successful applicationsin manufacturing scheduling for panel devices based on Hybrid MultiobjectiveEvolutionary Algorithms with TOPSIS.

Bio-Sketch：

Dr. Mitsuo Gen is asenior research scientist at Fuzzy Logic Systems Institute and visitingprofessor at Research Institute for Science and Technology, Tokyo University ofScience, Japan. Research Field:Evolutionary Computation, Manufacturing Scheduling, and Logistics. Society:President: APIEMS (2005.1 – 2006.12) & IMS (2010.8–2016.8), APIEMS: Fellow,SOFT: Honorary member, AreaEditor: Computers & Industrial Eng., Assoc. Editor: J. of Intelligent Manufacturing.