介紹討論數量分析方法之概念，包括Simulation Modeling, Comparisons and Evaluation of Alternative System Designs, Search Methods for Unconstrained and Constrained Optimization, Lagrange Duality and Optimality Conditions, Markov Chain and the Poisson Process, Introduction to Queuing Theory, Introduction to AI and Searching in Artificial Neural Networks, Searching in Genetic Algorithm, Stochastic Search, Kernel-based Searching Algorithms。Introduce and discuss the concepts of quantitative analysis methods, including Simulation Modeling, Comparisons and Evaluation of Alternative System Designs, Search Methods for Unconstrained and Constrained Optimization, Lagrange Duality and Optimality Conditions, Markov Chain and the Poisson Process, Introduction to Queuing Theory, Introduction to AI and Searching in Artificial Neural Networks, Searching in Genetic Algorithm, Stochastic Search, Kernel-based Searching Algorithms.
介紹討論數量分析方法之概念，培養學生於數量分析中最佳化方法之基本概念。
This part of the course is one of the 4 consecutive topics. This one is focused on the AI-Based search methods. The basic concepts and the major methods and models will be delivered in the lectures.
Introduce and discuss the concepts of quantitative analysis methods, and cultivate students' basic concepts of optimization methods in quantitative analysis.
This part of the course is one of the 4 consecutive topics. This one is focused on the AI-Based search methods. The basic concepts and the major methods and models will be delivered in the lectures.
第一部分授課教師：翁紹仁老師
1. Banks, J. and John S. Carson, II, Discrete-Event System Simulation, Prentice-Hall, 1984.
2. Winston, W. L., Operations Research: Applications and Algorithms, 2nd Ed., Duxbury Press, Belmont, California, 1991
第二部分授課教師：張炳騰老師
1. S. S. Rao, ENGINEERING OPTIMIZATION: THEORY AND PRACTICE, 3rd Edition, John Wiley & Sons, 1996.
2. G. N. Vanderplaats, NUMERICAL OPTIMIZATION TECHNIQUES FOR ENGINEERING DESIGN WITH APPLICATIONS, McGraw-Hill, 1994.
3. M. S. Bazaraa, H. D. Sherali and C. M. Shetty, NONLINEAR PROGRAMMING: THEORY AND ALGORITHMS, 2nd Edition, John Wiley & Sons, 1993.
第三部分授課教師：彭 泉老師
1. Goodman Roe, Introduction to Stochastic Models: Second Edition, 2006, Dover Publications, originally published by The Benjamin/Cummings Publishing Company, Inc., 1988, ISBN: 0486450376
第四部分授課教師：王偉華老師
1. Haykin, Simon, Neural Networks. (2nd edi )
2. Cristianini, Nello, An Introduction to Support Vector Machines.
3. Neapolitan, Richard E., Learning Bayesian Networks, Prentice Hall, 2004
Part One Teacher: Mr. Weng Shaoren
1. Banks, J. and John S. Carson, II, Discrete-Event System Simulation, Prentice-Hall, 1984.
2. Winston, W. L., Operations Research: Applications and Algorithms, 2nd Ed., Duxbury Press, Belmont, California, 1991
Part 2 teacher: Mr. Zhang Bingteng
1. S. S. Rao, ENGINEERING OPTIMIZATION: THEORY AND PRACTICE, 3rd Edition, John Wiley & Sons, 1996.
2. G. N. Vanderplaats, NUMERICAL OPTIMIZATION TECHNIQUES FOR ENGINEERING DESIGN WITH APPLICATIONS, McGraw-Hill, 1994.
3. M. S. Bazaraa, H. D. Sherali and C. M. Shetty, NONLINEAR PROGRAMMING: THEORY AND ALGORITHMS, 2nd Edition, John Wiley & Sons, 1993.
Part Three: Teacher Peng Quan
1. Goodman Roe, Introduction to Stochastic Models: Second Edition, 2006, Dover Publications, originally published by The Benjamin/Cummings Publishing Company, Inc., 1988, ISBN: 0486450376
Part 4 Teacher: Teacher Wang Weihua
1. Haykin, Simon, Neural Networks. (2nd edi)
2. Cristianini, Nello, An Introduction to Support Vector Machines.
3. Neapolitan, Richard E., Learning Bayesian Networks, Prentice Hall, 2004
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