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Possibilistic group support system for pricing and inventory problems

Possibilistic group support system for pricing and inventory problems Proposes a possibilistic group support system (PGSS) for the retailer pricing and inventory problem when possibilistic fluctuations of product parameters are controlled by a set of possibilistic optimality conditions. Experts in various functional areas convey their subjective judgement to the PGSS in the form of analytical models (for product parameters estimation), fuzzy concepts (facts), and possibilistic propositions (for validation and choice procedures). Basic probability assignments are used to elicit experts' opinions. They are then transformed into compatibility functions for fuzzy concepts using the falling shadow technique. Evidence is processed in the form of fuzzy concepts, then is rewritten back to basic probability assignments using the principle of least ignorance on randomness. The PGSS allows the user (inventory control) to examine a trade-off between the belief value of a greater profit and a lower amount of randomness associated with it. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Logistics Information Management Emerald Publishing

Possibilistic group support system for pricing and inventory problems

Logistics Information Management , Volume 13 (2): 9 – Apr 1, 2000

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Publisher
Emerald Publishing
Copyright
Copyright © 2000 MCB UP Ltd. All rights reserved.
ISSN
0957-6053
DOI
10.1108/09576050010313956
Publisher site
See Article on Publisher Site

Abstract

Proposes a possibilistic group support system (PGSS) for the retailer pricing and inventory problem when possibilistic fluctuations of product parameters are controlled by a set of possibilistic optimality conditions. Experts in various functional areas convey their subjective judgement to the PGSS in the form of analytical models (for product parameters estimation), fuzzy concepts (facts), and possibilistic propositions (for validation and choice procedures). Basic probability assignments are used to elicit experts' opinions. They are then transformed into compatibility functions for fuzzy concepts using the falling shadow technique. Evidence is processed in the form of fuzzy concepts, then is rewritten back to basic probability assignments using the principle of least ignorance on randomness. The PGSS allows the user (inventory control) to examine a trade-off between the belief value of a greater profit and a lower amount of randomness associated with it.

Journal

Logistics Information ManagementEmerald Publishing

Published: Apr 1, 2000

Keywords: Inventory; Inventory control; Logistics; Decision making

References