scholarly journals A Mathematical Model for Strategic Decision Making in Two Level Supply Chain Network Design

2013 ◽  
Vol 32 (3) ◽  
pp. 107-125
Author(s):  
Ki-Ho Chung
2015 ◽  
Vol 16 (04) ◽  
pp. 907-938 ◽  
Author(s):  
Xiaoyang Zhou ◽  
Yan Tu ◽  
Jing Han ◽  
Jiuping Xu ◽  
Xionghui Ye

In this paper, we concentrate on dealing with a class of decision-making problems with level-2 fuzzy coefficients. We first discuss how to transform a level-2 fuzzy decision-making model with expected objectives and chance constrained into crisp equivalent models, then an interactive fuzzy satisfying method is introduced to obtain the decision makers satisfying solution. In addition, the technique of level-2 simulations is applied to deal with general level-2 fuzzy models which are usually hard to be converted into their crisp equivalents. Furthermore, based on the level-2 fuzzy programming, we focus on the supply chain network design problem where the total transport costs and the customer demands are assumed to be level-2 fuzzy numbers, a hybrid intelligent algorithm based on GA is used to solve the general supply chain design model. Finally, a numerical example and a case study are presented to illustrate the effectiveness of the model and the algorithm.


2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Vincent F. Yu ◽  
Nur Mayke Eka Normasari ◽  
Huynh Trung Luong

This paper proposes integrated location, production, and distribution planning for the supply chain network design which focuses on selecting the appropriate locations to build a new plant and distribution center while deciding the production and distribution of the product. We examine a multiechelon supply chain that includes suppliers, plants, and distribution centers and develop a mathematical model that aims at minimizing the total cost of the supply chain. In particular, the mathematical model considers the decision of how many plants and distribution centers to open and where to open them, as well as the allocation in each echelon. The LINGO software is used to solve the model for some problem cases. The study conducts various numerical experiments to illustrate the applicability of the developed model. Results show that, in small and medium size of problem, the optimal solution can be found using this solver. Sensitivity analysis is also conducted and shows that customer demand parameter has the greatest impact on the optimal solution.


2021 ◽  
Vol 13 (5) ◽  
pp. 2596
Author(s):  
Kanokporn Kungwalsong ◽  
Chen-Yang Cheng ◽  
Chumpol Yuangyai ◽  
Udom Janjarassuk

A supply chain disruption is an unanticipated event that disrupts the flow of materials in a supply chain. Any given supply chain disruption could have a significant negative impact on the entire supply chain. Supply chain network designs usually consider two stage of decision process in a business environment. The first stage deals with strategic levels, such as to determine facility locations and their capacity, while the second stage considers in a tactical level, such as production quantity, delivery routing. Each stage’s decision could affect the other stage’s result, and it could not be determined individual. However, supply chain network designs often fail to account for supply chain disruptions. In this paper, this paper proposed a two-stage stochastic programming model for a four-echelon global supply chain network design problem considering possible disruptions at facilities. A modified simulated annealing (SA) algorithm is developed to determine the strategic decision at the first stage. The comparison of traditional supply chain network decision framework shows that under disruption, the stochastic solutions outperform the traditional one. This study demonstrates the managerial viability of the proposed model in designing a supply chain network in which disruptive events are proactively accounted for.


2020 ◽  
Vol 11 (3) ◽  
pp. 63-120
Author(s):  
Monalisha Pattnaik

This study is based on a real-life case study of a SCND of a single milk product (premium milk) of a leading milk producing organization in Odisha. This product is highly perishable in nature; SCND implicates decision-making at a strategic level. Network design is the basis for the efficient operation of supply chain, and consequently, one of the most important problems a supply chain manager has to solve. This study conducts a real-life case-based modeling to address the gap in the area of supply chain network design. The author investigates the milk supply chain network design under preservation technology and propose a generic mathematical model for milk supply chain network design encompassing economic objective. A customized mathematical model is also developed for a leading milk producing organization in Odisha. Both of the models are formulated and solved by using piecewise nonlinear optimization.


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