A hybrid fuzzy bi-objective delivery planning model for leagile e-tailing under uncertainty

The rapid growth of e-business has paved the way for traditional retailers to distribute their items via the Internet. The success of online retailers (e-tailers) in the extremely competitive online marketplace depends on providing a beneficial and efficient scheme for customers' orders fulfill...

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Bibliographic Details
Published in:International journal of management science and engineering management Vol. 10; no. 1; pp. 62 - 72
Main Authors: Razmi, Jafar, Hassani, Anis, Babazadeh, Reza
Format: Journal Article
Language:English
Published: Taylor & Francis 02.01.2015
Subjects:
delivery planning
leagile
online retailer
optimization method
pricing
uncertainty
ISSN:1750-9653, 1750-9661
Online Access:Get full text
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Summary:The rapid growth of e-business has paved the way for traditional retailers to distribute their items via the Internet. The success of online retailers (e-tailers) in the extremely competitive online marketplace depends on providing a beneficial and efficient scheme for customers' orders fulfillment. In this paper, a joint model of pricing and online fulfillment assignment is presented for a distribution system in which a supplier sells items through an e-tail channel under the possibility of using substitute items with the satisfaction of customers' demands and delivery times. The aim of the model is to be 'lean' by minimizing operational cost and 'agile' through providing quick simultaneous reactions to market changes. We present a hybrid fuzzy bi-objective nonlinear programming model which is composed of a qualitative objective related to customers' satisfaction and a quantitative objective function, i.e. the maximization of revenue minus the total cost. After applying an appropriate strategy to defuzzify the model, the equivalent bi-objective crisp model is solved by an interactive fuzzy goal programming method to handle goals as well as their imprecise target levels simultaneously in order to find an efficient compromise solution. Moreover, an illustrative example is provided in order to prove the usefulness and efficiency of the proposed model and the solution approach.
ISSN:1750-9653
1750-9661
DOI:10.1080/17509653.2014.962110