Nested Partitions Method Theory And Applications
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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 ).
Nested Partitions Method, Theory and Applications
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 ).
Applications of Multi-Criteria and Game Theory Approaches
Author: Lyes Benyoucef
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-10-17
Aligning the latest practices, innovations and case studies with academic frameworks and theories, the broad area of multi-criteria and game theory applications in manufacturing and logistics is covered in comprehensive detail. Divided into two parts, part I is dedicated to ‘multi-criteria applications’ and includes chapters on logistics with a focus on vehicle routing problems, a multi-objective decision making approach to select the best storage policy and an exploratory study to predict the most important factors that can lead to successful mobile supply chain management adoption for manufacturing firms. Part II covers ‘game theory applications’ and encompasses the process of forming a coalition within a corporate network to the problem of integrating inventory and distribution optimization together with game theory to effectively manage supply networks. Providing a forum to investigate, exchange novel ideas and disseminate knowledge covering the broad area of multi-criteria and game theory applications in manufacturing and logistics, Applications of Multi-Criteria and Game Theory Approaches is an excellent reference for students, researchers but also managers and industry professionals working with manufacturing and logistics issues.