Anticipatory Optimization for Dynamic Decision Making (Record no. 106255)

000 -LEADER
fixed length control field 04534nam a22004695i 4500
001 - CONTROL NUMBER
control field 978-1-4614-0505-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220083732.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110622s2011 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461405054
-- 978-1-4614-0505-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-0505-4
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HD30.23
072 #7 - SUBJECT CATEGORY CODE
Subject category code KJT
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code KJMD
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS049000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.40301
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Meisel, Stephan.
Relator term author.
245 10 - TITLE STATEMENT
Title Anticipatory Optimization for Dynamic Decision Making
Medium [electronic resource] /
Statement of responsibility, etc by Stephan Meisel.
264 #1 -
-- New York, NY :
-- Springer New York,
-- 2011.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 182 p.
Other physical details online resource.
336 ## -
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-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Operations Research/Computer Science Interfaces Series,
International Standard Serial Number 1387-666X ;
Volume number/sequential designation 51
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Basic Concepts and Definitions -- Perfect Anticipation -- Synergies of Optimization and Data Mining -- Approximate Anticipation -- Dynamic Vehicle Routing -- Anticipatory Routing of a Service Vehicle -- Computational Study -- Managerial Impact of Anticipatory Optimization -- Conclusions.
520 ## - SUMMARY, ETC.
Summary, etc The availability of today’s online information systems rapidly increases the relevance of dynamic decision making within a large number of operational contexts. Whenever a sequence of interdependent decisions occurs, making a single decision raises the need for anticipation of its future impact on the entire decision process. Anticipatory support is needed for a broad variety of dynamic and stochastic decision problems from different operational contexts such as finance, energy management, manufacturing and transportation. Example problems include asset allocation, feed-in of electricity produced by wind power as well as scheduling and routing. All these problems entail a sequence of decisions contributing to an overall goal and taking place in the course of a certain period of time. Each of the decisions is derived by solution of an optimization problem. As a consequence a stochastic and dynamic decision problem resolves into a series of optimization problems to be formulated and solved by anticipation of the remaining decision process. However, actually solving a dynamic decision problem by means of approximate dynamic programming still is a major scientific challenge. Most of the work done so far is devoted to problems allowing for formulation of the underlying optimization problems as linear programs. Problem domains like scheduling and routing, where linear programming typically does not produce a significant benefit for problem solving, have not been considered so far. Therefore, the industry demand for dynamic scheduling and routing is still predominantly satisfied by purely heuristic approaches to anticipatory decision making. Although this may work well for certain dynamic decision problems, these approaches lack transferability of findings to other, related problems. This book has serves two major purposes: ‐ It provides a comprehensive and unique view of anticipatory optimization for dynamic decision making. It fully integrates Markov decision processes, dynamic programming, data mining and optimization and introduces a new perspective on approximate dynamic programming. Moreover, the book identifies different degrees of anticipation, enabling an assessment of specific approaches to dynamic decision making. ‐ It shows for the first time how to successfully solve a dynamic vehicle routing problem by approximate dynamic programming. It elaborates on every building block required for this kind of approach to dynamic vehicle routing. Thereby the book has a pioneering character and is intended to provide a footing for the dynamic vehicle routing community.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Economics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical optimization.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Economics/Management Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Operations Research/Decision Theory.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Operations Research, Management Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Optimization.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781461405047
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Operations Research/Computer Science Interfaces Series,
-- 1387-666X ;
Volume number/sequential designation 51
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-0505-4
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