<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>Modeling with Stochastic Programming</title>
  </titleInfo>
  <name type="personal">
    <namePart>King, Alan J.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">aut</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/aut</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Wallace, Stein W.</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">aut</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/aut</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>SpringerLink (Online service)</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">sz</placeTerm>
    </place>
    <dateIssued encoding="marc">2024</dateIssued>
    <edition>2nd ed. 2024.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">electronic</form>
    <form authority="gmd">electronic resource</form>
    <reformattingQuality>access</reformattingQuality>
    <extent>XVIII, 202 p. 34 illus., 15 illus. in color. online resource.</extent>
  </physicalDescription>
  <abstract>This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.</abstract>
  <tableOfContents>Uncertainty in Optimization -- Information Structures and Feasibility -- Modeling the Objective Function -- Scenario Tree Generation, With Michal Kaut and Jamie Fairbrother -- High-Dimentional Dependent Randomness. With Zhaoxia Guo and Michal Kaut -- Service Network Design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A Multi-dimensional Newsboy Problem with Substitution, With Hajnalka Vaagen -- References -- Index.</tableOfContents>
  <note type="statement of responsibility">by Alan J. King, Stein W. Wallace.</note>
  <subject authority="lcsh">
    <topic>Probabilities</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Operations research</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Mathematical optimization</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Numerical analysis</topic>
  </subject>
  <subject>
    <topic>Probability Theory</topic>
  </subject>
  <subject>
    <topic>Operations Research and Decision Theory</topic>
  </subject>
  <subject>
    <topic>Optimization</topic>
  </subject>
  <subject>
    <topic>Numerical Analysis</topic>
  </subject>
  <classification authority="lcc">QA273.A1-274.9</classification>
  <relatedItem type="host">
    <titleInfo>
      <title>Springer Nature eBook</title>
    </titleInfo>
  </relatedItem>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="series">
    <titleInfo>
      <title>Springer Series in Operations Research and Financial Engineering</title>
    </titleInfo>
  </relatedItem>
  <identifier type="isbn">9783031545504</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-54550-4</identifier>
  <location>
    <url>https://doi.org/10.1007/978-3-031-54550-4</url>
  </location>
  <recordInfo>
    <recordCreationDate encoding="marc">240531</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251030112245.0</recordChangeDate>
    <recordIdentifier source="DE-He213">978-3-031-54550-4</recordIdentifier>
  </recordInfo>
</mods>
