Multi-objective bi-level supply chain network order allocation problem under fuzziness

In this paper we addressed supply chain network (SCN) as bi-level programming problem in which the primary objective is to determine optimal order allocation of products where the customer’s demands and supply for the products are fuzzy. In the proposed SCN model, we suppose that the first level (le...

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Bibliographic Details
Published in:Opsearch Vol. 55; no. 3-4; pp. 721 - 748
Main Authors: Gupta, Srikant, Ali, Irfan, Ahmed, Aquil
Format: Journal Article
Language:English
Published: New Delhi Springer India 01.11.2018
Springer Nature B.V
Subjects:
Application Article
Business and Management
Goal programming
Management
Mathematical models
Mathematics
Multiple objective analysis
Operations research
Operations Research/Decision Theory
Supply chains
Warehouses
Supply chain network
Fuzzy goal programming
Multi-objective optimization
Bi-level programming problem
cut approach
Trapezoidal fuzzy number
ISSN:0030-3887, 0975-0320
Online Access:Get full text
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Summary:In this paper we addressed supply chain network (SCN) as bi-level programming problem in which the primary objective is to determine optimal order allocation of products where the customer’s demands and supply for the products are fuzzy. In the proposed SCN model, we suppose that the first level (leader) and second level (follower) operate two separate groups of SCN. The leader, who moves first, determines quantities shipped to retailers, and then, the follower decides his quantities rationally. The leader’s objective is to minimize the total transportation costs, and similarly, the follower’s objective is to minimize the total delivery time of the SCN and at the same time balancing the optimal order allocation from each source, plant, retailer and warehouse respectively. The fuzzy goal programming approach has been used to achieve the highest degree of the membership goals by minimizing the deviational variables so that most satisfactory or the preferred solution for both the levels to be obtained. A numerical example is given to demonstrate the proposed methodology.
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ISSN:0030-3887
0975-0320
DOI:10.1007/s12597-018-0340-2