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Formulating and solving Warehouse location problems
Details
Warehouse location problem (WLP) is a variant of the well known facility location problem. It is about taking a decision to choose warehouses amongst a set of known locations between plants and markets, such that total cost of location and transportation is minimized. WLP is formulated as Mixed Integer Programming (MIP) problem. Three variants of WLP have been attempted in this work by varying the capacity considerations and changing the warehouse echelons. These variants are Single Stage Uncapacitated Warehouse Location Problem (SSUWLP), Single Stage Capacitated Warehouse Location Problem (SSCWLP), and Two Stage Capacitated Warehouse Location Problem (TSCWLP). These variants being NP-hard, obtaining optimal solution in practical time is difficult. The book aims to derive better method to attempt these problems by developing new solution approaches and better relaxations, which are used in branch-and-bound to get the optimal solution. The computational experiences of a large variety of small and large problems are analyzed. A key features of this work is an extensively studied literature of WLP. This book should help those who are working in the location problems or MIP problems.
Autorentext
A GIS-Business Analyst at NorthSouth GIS.Graduated Delhi University, PGDGIS from University of Salzburg, Austria& M.Sc Geo informatics from Symbiosis International University, India.Earlier Associated with Central Road Research Institute, BSES& MapmyIndia. Active member of The Image and Geospatial Information Society & American Planning Association
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783659231186
- Sprache Englisch
- Größe H220mm x B220mm x T150mm
- Jahr 2012
- EAN 9783659231186
- Format Kartonierter Einband (Kt)
- ISBN 978-3-659-23118-6
- Titel Formulating and solving Warehouse location problems
- Autor Priyanka Verma
- Untertitel Approach for finding optimal solution to the well known NP- Hard problem
- Herausgeber LAP Lambert Academic Publishing
- Anzahl Seiten 272
- Genre Wirtschaft