Ordinal Optimization
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Ordinal Optimization
Author: Yu-Chi Ho
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-01-23
Performance evaluation of increasingly complex human-made systems requires the use of simulation models. However, these systems are difficult to describe and capture by succinct mathematical models. The purpose of this book is to address the difficulties of the optimization of complex systems via simulation models or other computation-intensive models involving possible stochastic effects and discrete choices. This book establishes distinct advantages of the "softer" ordinal approach for search-based type problems, analyzes its general properties, and shows the many orders of magnitude improvement in computational efficiency that is possible.
Nested Partitions Method, Theory and Applications
Author: Leyuan Shi
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-10-30
Thesubjectofthisbookisthenested partitions method(NP),arelativelynew optimization method that has been found to be very e?ective solving discrete optimization problems. Such discrete problems are common in many practical applications and the NP method is thus useful in diverse application areas. It can be applied to both operational and planning problems and has been demonstrated to e?ectively solve complex problems in both manufacturing and service industries. To illustrate its broad applicability and e?ectiveness, in this book we will show how the NP method has been successful in solving complex problems in planning and scheduling, logistics and transportation, supply chain design, data mining, and health care. All of these diverse app- cationshaveonecharacteristicincommon:theyallleadtocomplexlarge-scale discreteoptimizationproblemsthatareintractableusingtraditionaloptimi- tion methods. 1.1 Large-Scale Optimization IndevelopingtheNPmethodwewillconsideroptimization problemsthatcan be stated mathematically in the following generic form: minf(x), (1.1) x?X where the solution space or feasible region X is either a discrete or bounded ? set of feasible solutions. We denote a solution to this problem x and the ? ? objective function value f = f (x ).
Applied Mechanics, Mechatronics and Intelligent Systems - Proceedings of the 2015 International Conference (ammis2015)
This book consists of one hundred and twenty-five selected papers presented at the 2015 International Conference on Applied Mechanics, Mechatronics and Intelligent Systems (AMMIS2015), which was held in Nanjing, China during June 19-20, 2015.AMMIS2015 focuses on seven main areas, namely, applied mechanics, control and automation, intelligent systems, computer technology, electronics engineering, electrical engineering, and materials science and technology. Experts in this field from all over the world contributed to the collection of research results and development activities.AMMIS2015 provides an excellent international exchange platform for researchers to share their development works and results in these areas. All papers selected for this proceeding were subjected to a rigorous peer-review process.