A multi-objective stochastic programming approach for supply chain design considering risk

2008 ◽  
Vol 116 (1) ◽  
pp. 129-138 ◽  
Author(s):  
A. Azaron ◽  
K.N. Brown ◽  
S.A. Tarim ◽  
M. Modarres
Keyword(s):  
Supply Chain ◽  
Stochastic Programming ◽  
Supply Chain Design ◽  
Programming Approach ◽  
Multi Objective

Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis

2019 ◽  
Vol 273 (3) ◽  
pp. 1149-1164 ◽  
Author(s):  
S.U.K. Rohmer ◽  
J.C. Gerdessen ◽  
G.D.H. Claassen
Keyword(s):  
Supply Chain ◽  
Food System ◽  
Supply Chain Design ◽  
Objective Analysis ◽  
Sustainable Supply Chain ◽  
Multi Objective

scholarly journals The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Selection Problem ◽  
Programming Approach ◽  
Vendor Selection ◽  
Chain Management ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

A multi-stage stochastic programming approach for supply chain risk mitigation via product substitution

2020 ◽  
Vol 149 ◽  
pp. 106786
Author(s):  
Seyed Mahdi Ghorashi Khalilabadi ◽  
Seyed Hessameddin Zegordi ◽  
Ehsan Nikbakhsh
Keyword(s):  
Supply Chain ◽  
Stochastic Programming ◽  
Risk Mitigation ◽  
Programming Approach ◽  
Product Substitution ◽  
Supply Chain Risk ◽  
Multi Stage

Fuzzy programming approach to multi-objective stochastic programming problems when bi's follow joint normal distribution

2000 ◽  
Vol 109 (1) ◽  
pp. 91-96 ◽  
Author(s):  
S.B. Sinha ◽  
Suwarna Hulsurkar ◽  
M.P. Biswal
Keyword(s):  
Stochastic Programming ◽  
Normal Distribution ◽  
Fuzzy Programming ◽  
Programming Approach ◽  
Multi Objective

Coordinated Contract Decisions in a Make-to-Order Manufacturing Supply Chain: A Stochastic Programming Approach

2012 ◽  
Vol 22 (3) ◽  
pp. 642-660 ◽  
Author(s):  
Yan Feng ◽  
Alain Martel ◽  
Sophie D'Amours ◽  
Robert Beauregard
Keyword(s):  
Supply Chain ◽  
Stochastic Programming ◽  
Programming Approach ◽  
Make To Order ◽  
Manufacturing Supply Chain
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