Nested partitions method, theory and applications
type: Item
instance of: scholarly article
title: Nested partitions method, theory and applications
zbMATH Open document ID: 1159.90003
DOI: 10.1007/978-0-387-71909-2
author: Sigurdur Ólafsson
author: Shi, Leyuan
publication date: 2008-06-30T00:00:00Z
review text: This book is devoted to a relatively new optimization method that has been found to be very effective in solving discrete optimization problems. The subject nested partitions method (NP) is an innovative mix of traditional optimization methodology and probabilistic assumptions. The Nested Partitions (NP) framework combines many well-known optimization techniques, including dynamic programming, mixed integer programming, genetic algorithms and tabu search and also integrates many problem specific local search heuristics. In this book, the authors 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. The book is intended to be a reference material for researchers and practitioners in management science, industrial engineering, economics, computer science, and environmental science. Also, because of its emphasis on practical applications, the book can appropriately be used as a textbook in a graduate course. I feel this intension is more or less fulfilled. The book is organized in two parts. Part I develops the general theory and implementation framework for the NP method, while Part II provides a detailed look at several application areas. Chapter 1 presents an introduction to large scale optimization, exact solution methods, heuristic solution methods, NP method and application examples that illustrate the type of optimization problems for which the NP method is particularly effective. Chapter 2 develops the foundation for the NP method and its implementation. Chapter 3 focuses on the special case where the objective function is not known analytically but must be estimated and is hence noisy. This introduces additional challenges but the NP method can still be applied effectively. This chapter discusses what makes the NP method effective for problems with noisy performance, provides a convergence analysis, and suggests how the NP method is bes…
reviewed by: Samir Kumar Neogy
Mathematics Subject Classification ID: 90-01
Mathematics Subject Classification ID: 90-02
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 90C11
Mathematics Subject Classification ID: 90C10
zbMATH DE Number: 5294580
zbMATH Keywords: combinatorial optimization
zbMATH Keywords: meta-heuristics
zbMATH Keywords: mixed integer programming
zbMATH Keywords: optimization
describes a project that uses: DistAl
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-0-387-71909-2
OpenAlex ID: W630732584
published in: International Series in Operations Research & Management Science
description: scientific article; zbMATH DE number 5294580