Prof. Andrew K.S. Jardine, PhD, P.Eng., CEng, FCAE, FIIE, FISEAM (Hon.)
Professor Emeritus, Industrial Engineering Research: Manufacturing; operations research; Centre for Maintenance Optimization and Reliability Engineering (C-MORE), industry-guided real-world research for optimal asset management.

Dr. Andrew K.S. Jardine is Founding Director of the Centre for Maintenance Optimization & Reliability Engineering (C-MORE). He is author of economic life software AGE/CON and PERDEC, licensed to organizations in the transportation, mining, electrical utilities, and process industries, and author of OREST software used for optimizing component preventive replacement decisions and forecasting demand for spare parts. Dr. Jardine is a prolific researcher and advocate of advances in maintenance decision-making and reliability engineering...

Prof. Paolo Toth
Emeritus , College of Engineering
Adjunct Professor
Vice-President of the School of Engineering and Architecture - Bologna
Academic disciplines: MAT / 09 Operational Research
From August to October 1987 he was Visiting Professor of Routing and Scheduling Problems at the Graduate School of Industrial Administration of the Carnegie Mellon University, Pittsburgh, USA.
He acted as Supervisor of 20 Ph.D. students.
His current main research interests include Operational Research and Mathematical Programming methodologies and, in particular, the design and implementation of effective exact and heuristic algorithms for Combinatorial Optimization and Graph Theory problems, and their application to real-world Transportation, Logistics, Loading, Routing, Crew Management, Railway Optimization problems.
Professor Toth was the President of IFORS.
Click here to view his abstract.

Prof. XIE, Min
MSc(KTH, Sweden), LicTech(Linkoping), PhD(Linkoping, Sweden)
Chair Professor of Industrial Engineering
Associate Dean (Internationalization), College of Science and Engineering

Research Interests

  • • Reliability Engineering
  • • Quality Management
  • • Software Reliability
  • • Applied Statistics

Awards and Achievements

  • Fellow of IEEE (1 Jan 2006)
  • Fellow of Institution of Engineers Singapore (2005)
  • William Mong visiting research fellow at Univ of Hong Kong (1996)
  • Lee Kuan Yew research fellowship, Singapore (1991)
  • Youngest PhD graduate at Linkoping University, Sweden (1987)

Srinivas Chakravarthy
Kettering University, Flint, Michigan, USA

Dr. Srinivas R. Chakravarthy, professor of Industrial Engineering
Ph.D. in Operations Research from the Department of Mathematical Sciences at the University of Delaware, with expertise in applied probability, applied statistics, mathematics, operations research, reliability and stochastic modeling.

Dr. Mitsuo Gen
Fuzzy Logic Systems Institute and Tokyo University of Science, Japan

Dr. Gen is a senior research scientist at Fuzzy Logic Systems Institute and visiting professor at Research Institute for Science and Technology, Tokyo University of Science, Japan. PhD in Engineering, Kogakuin University and PhD in Informatics, Kyoto University.
His research interests are Evolutionary Computation, Manufacturing Scheduling, Logistics and Decision Making.

Abstract of the talk:

In the real world manufacturing systems there are many combinatorial optimization problems (COP) imposing on more complex issues, such as complex structure, nonlinear constraints, and multiple objectives to be handled simultaneously and make the problem intractable to the traditional approaches because of NP-hard COP. For developing an efficient algorithm whose computational time is small, or at least reasonable for NP-hard combinatorial problems met in practice, we have to consider the following very important issues: - quality of solution, - computational time, and - effectiveness of the nondominated solutions for multiobjective optimization problem (MOP).
Evolutionary algorithm (EA) is a subset of metaheuristics, a generic population-based metaheuristic such as genetic algorithm (GA), particle swarm optimization (PSO), and estimation of distribution algorithm (EDA). EA is based on principles from evolution theory, and it is very powerful, and broadly applicable stochastic search and optimization technique which is effective for solving various NP hard COP models.This invited lecture will be firstly introduced a brief survey of several metaheuristics based on EA such as GA, hybrid GA (HGA), multiobjective GA (MoGA), PSO and EDA for applying to various combinatorial optimization problems. Secondly real applications based on hybrid metaheuristics will summarize the following recent semiconductor scheduling topics:
1. Semiconductor Final Testing Scheduling,
2. HDD Manufacturing Scheduling,
3. TFT-LCD Module Assembly Scheduling