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Practice-driven Solutions for Invent...

Wang, Le.

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Practice-driven Solutions for Inventory Management Problems in Data-scarce Environments.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Practice-driven Solutions for Inventory Management Problems in Data-scarce Environments./
Author:	Wang, Le.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	112 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-12, Section: A.
Contained By:	Dissertations Abstracts International80-12A.
Subject:	Management. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13882671
ISBN:	9781392242773

Practice-driven Solutions for Inventory Management Problems in Data-scarce Environments.
Wang, Le.

Practice-driven Solutions for Inventory Management Problems in Data-scarce Environments. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 112 p.

Source: Dissertations Abstracts International, Volume: 80-12, Section: A.

Thesis (Ph.D.)--Boston University, 2019.

This item must not be sold to any third party vendors.

Many firms are challenged to make inventory decisions with limited data, and high customer service level requirements. This thesis focuses on heuristic solutions for inventory management problems in data-scarce environments, employing rigorous mathematical frameworks and taking advantage of the information that is available in practice but often ignored in literature. We define a class of inventory models and solutions with demonstrable value in helping firms solve these challenges.

ISBN: 9781392242773Subjects--Topical Terms:

516664
Management.

Practice-driven Solutions for Inventory Management Problems in Data-scarce Environments.
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500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Joglekar, Nitin R.
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520 $a Many firms are challenged to make inventory decisions with limited data, and high customer service level requirements. This thesis focuses on heuristic solutions for inventory management problems in data-scarce environments, employing rigorous mathematical frameworks and taking advantage of the information that is available in practice but often ignored in literature. We define a class of inventory models and solutions with demonstrable value in helping firms solve these challenges.
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