Global supply chain network design problem with rules of origin and limited import quotas

Kybernetes ◽  
2019 ◽  
Vol 48 (5) ◽  
pp. 930-948 ◽  
Author(s):  
Xinxuan Cheng ◽  
Guoqing Yang ◽  
Longfei Fan

Purpose This paper aims to develop an uncertain global supply chain network design (GSCND) model with rules of origin (RoOs) and limited import quotas, and to discuss the international factors’ effects on location decisions. Design/methodology/approach The authors establish an uncertain GSCND model with the international factors. The transportation costs and customers’ demands are characterized as random variables. To deal with the risk of uncertainty, the authors introduce the customers’ demand service level. A sample approximation approach (SAA) is used to deal with the service level constraint and turn the proposed model into a mixed integer programming. On the basis of the properties of the proposed model, a hybrid memetic algorithm (MA) is designed to solve it. Findings The authors find that the proposed MA is efficient to the real supply chain network design problem. Besides, the RoOs and limited import quotas can affect the optimal choices of plant and distribution center locations. Originality/value The authors propose an uncertain GSCND model with RoOs and limited import quotas. An MA with SAA is designed to solve the proposed model. The authors apply the proposed model into a real global supply chain of an apparel corporation in East Asia, and give some managerial insights.

2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm

Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.


2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.


2019 ◽  
Vol 31 (3) ◽  
pp. 467-490 ◽  
Author(s):  
Asama Alglawe ◽  
Andrea Schiffauerova ◽  
Onur Kuzgunkaya ◽  
Itad Shiboub

Purpose The purpose of this paper is to explore the impact of the cost of quality (COQ) expenditure allocations on a capacitated supply chain (SC) network. Design/methodology/approach This paper proposes a non-linear optimization model which integrates the opportunity cost (OC) (i.e. customer satisfaction cost), into the COQ with consideration of the QL in the supply chain network design decisions. In addition, it examines the effect of considering an investment at each SC echelon to ensure the best overall QL. A numerical example is presented to illustrate the behavior of the model. Findings The results show how the QL, COQ and facility location decisions change when incorporating the OC, investments and transportation costs into the SC model. Originality/value The novelty of this paper is that it considers the effect of OC, investment at each echelon and transportation costs on SC design by minimizing the overall spending on the COQ. These issues have not been explored, and for that reason, this paper contributes to the understanding of the critical factors that optimizes the SC COQ.


2017 ◽  
Vol 254 (1-2) ◽  
pp. 533-552 ◽  
Author(s):  
Xiaoge Zhang ◽  
Andrew Adamatzky ◽  
Felix T. S. Chan ◽  
Sankaran Mahadevan ◽  
Yong Deng

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