Ehsan Mardan; Rezvane Kashani; Reza Kamranrad
Volume 10, Issue 1 , July 2023, , Pages 34-52
Abstract
Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. ...
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Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. The present study was an attempt to propose an emergency order and production planning for a multi-product multi-item problem where products are made up of several ingredients. A side from the main supplier, the backup supplier can be used to supply each component where orders must be delivered within a certain time interval (specified time window). In the present study attempts are made to use sourcing strategies to realize supply chain flexibility under disruptions. A scenario-based mathematical model encompassing different uncertainties such as those arising from disruption and operational risks is formulated. A case study analysis is carried out to appraise the output of risk attitudes adopted by different decision-makers (both risk-neutral and risk-averse). The present study presents strategies to create flexible supply bases that diminish the cost of the worst scenario in the face of supply chain risks. By increasing the number of primary and supporting suppliers, VAR and C-VR values will increase, so the management offer is that the number of suppliers should be kept constant within acceptable limits to prevent a sharp increase in the number of suppliers. Suppliers should release orders in time by establishing time windows and setting deadlines in order to receive orders. Also, this paper shows that the values of VAR and C-VR decrease with the increase of primary supply capacity, and with the increase of primary supply capacity, costs are reduced by about 99%, which reduces the effect of disruption on the capacity of primary suppliers.
Somayeh Najafi-Ghobadi; Mahtab Sherafati
Abstract
Nowadays, supply chains have been facing significant economic forfeitures because of unpredicted disruptions. Furthermore, managers try to design sustainable and reliable supply chains. In this paper, we present an inventory-location model to propound a reliable three echelon supply chain which includes ...
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Nowadays, supply chains have been facing significant economic forfeitures because of unpredicted disruptions. Furthermore, managers try to design sustainable and reliable supply chains. In this paper, we present an inventory-location model to propound a reliable three echelon supply chain which includes a production plant, distribution centers, and retailers. The production plant distributes a single product to retailers through distribution centers that are at risk of disruption. We considered reactive (consider backup distribution center for each retailer) and proactive (distribution center fortification) activates to enhance the supply chain's reliability. The proposed model indicates the location of distribution centers (DCs), the DCs that must be fortified, the allocation of retailers to DCs, and the inventory policy of DCs. The problem is formulated as a nonlinear integer programming model. Since our model is an NP-hard problem, we provide a Lagrangian relaxation algorithm to solve it. Numerical examples demonstrate the computational efficiency of the proposed solution algorithm. Results show that, with increasing the budget of fortification, the total expected cost will decrease. A higher inventory cost leads to an increase in the number of opened DCs, while higher ordering cost and the transportation cost from production plant to DCs decrease the number of opened DCs. Among other results, the number of opened DCs is positively affected by the cost of transporting from DCs to retailers.
Seyed Ali Alavikia; Mohammad Taghi TaghaviFard; Maghsoud Amiri; Parham Azimi
Abstract
However, there is a lot of capital and plenty of manpower in the auto spare part industry, the enterprises and supply chains of this industry do not perform well in our country. This research models a three-level supply chain with multiple manufacturers, distribution centers and retailers, to minimize ...
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However, there is a lot of capital and plenty of manpower in the auto spare part industry, the enterprises and supply chains of this industry do not perform well in our country. This research models a three-level supply chain with multiple manufacturers, distribution centers and retailers, to minimize the total cost by taking into account various disruptions. The database of two active car spare parts companies for five strategic products in one year has been used. Then, the mathematical model is analyzed by considering disruptions based on three different sales policies: back orders, lost sales and outsourcing. Besides, to evaluate the performance of the model some numerical examples are used and analyzed to determine that algorithm works. Model solved efficiently by MATLAB software. The results show that the proposed algorithm of this research can neutralize the effect of the disruptions and cause a significant reduction in total cost of the system. The model is useful for helping decision makers to adopt an active approach to maintaining business benefits when disruptions take place in the supply chain.
Masoud Rabbani; Leyla Aliabadi; Razieh Heidari; Hamed Farrokhi-Asl
Abstract
This study considers a reliable location – inventory problem for a supply chain system comprising one supplier, multiple distribution centers (DCs), and multiple retailers in which we determine DCs location, inventory replenishment decisions and assignment retailers to DCs, simultaneously. Each ...
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This study considers a reliable location – inventory problem for a supply chain system comprising one supplier, multiple distribution centers (DCs), and multiple retailers in which we determine DCs location, inventory replenishment decisions and assignment retailers to DCs, simultaneously. Each DC is managed through a continuous review (S, Q) inventory policy. For tackling real world conditions, we consider the risk of probabilistic distribution center disruptions, and also uncertain demand and lead times, which follow Poisson and Exponential distributions, respectively. A new mathematical formulation is proposed and we model the proposed problem in two steps, in the first step, a queuing system is applied to calculate mean inventory and mean reorder rate of steady-state condition for each DC. Next, regarding the results obtained from the first step, we formulate a mixed integer nonlinear programming model which minimizes the total expected cost of inventory, location and transportation and can be solved efficiently by means of LINGO software. Finally, several test problems and sensitivity analysis of key parameters are conducted in order to illustrate the effectiveness of the proposed model.