فصلنامه مدیریت زنجیره تامین
پیاپی 65 (زمستان 1398)

By increasing population and consequently the increasing demand for freight, proper design of transport networks is increasingly important. Given this, the use of hubs in the transport network with indirectly connection between the source and destination nodes significantly reduces costs and the number of routes. To transform the country into a commercial hub, the development of logistics centers, including dry ports with an international approach, can be fruitful. One of the main features of the hub is the indirect connection of the nodes of origin to the destination, which increases the shipment time, but sometimes causes corruption of the goods. In this study, the design of a transport network has been focused on dry port location, which makes the hub location model flexible by allowing direct connection from source to destination. The mathematical model presented is solved using CPLEX in Gams. Then, by analyzing the sensitivity of the number of ports, it was emphasized the necessity of creating dry ports to reduce transportation costs.

Nowadays, the transfer of blood products to emergency and relief services has become increasingly important, given that blood has no substitute and that humans themselves are the source of its production, as well as advances in medical science that have led to surgical and therapeutic approaches. A new one has made the need to supply blood products less expensive and time-consuming in the modern age, hence the location of blood collection and storage centers and their distances from demand points to raise the level of service. Given the importance of the topic in this research to modeling a chain, it is abundant The purpose of blood products has been to meet two specific goals, namely to reduce costs and service time of the chain by considering different local and regional blood transfusion centers and selecting the optimal location of mobile blood centers, as well as by considering hospital demand centers and Accidental points have been tried to create a suitable network of supply chains near these points. Finally, the model is implemented as a case study with information obtained from the location of units in Zanjan city and is analyzed through meta-heuristic algorithm and results obtained have been analyzed.

As supply chains and its distribution centres expand, risk increases and can have very different impacts on the optimal inventory management policies to meet consumer demand. The basic idea of risk pooling in supply chains is that if the customer demands from all sources are pooled by a centralized system, then not only will expected profits increase, but also inventory levels and costs will decrease. Regarding to customer demand variability of textile clothing products, efficient inventory management in clothing supply chain leads to total inventory cost reduction, and then retaining competitive edge. In this paper, the effect of customer demand uncertainty in multiple warehouses system under the two centralized and decentralized systems is taken into consideration in the presence of deterministic supply. In order to investigate the effect of risk pooling and its result under two scenarios in (s,S) inventory control namely, 1) stochastic demand 2) stochastic demand and lead-time, a two-echelon clothing supply chain is taken into account under the aforementioned scenarios. We consider customer demand variability in a single manufacturer, multiple distribution centers and multiple retailers (demand points). We also assume that inventory is stored at only a single echelon, distribution centers, in order to make decisions about centralization versus decentralization of supply chain under consideration. In the latter part of this paper, aggregate warehouse is then located by logistical costs minimization through a real case study. In doing so, different transportation modes, their related costs and distances from the centralized distribution center are involved by comparing potential location sites for the obtained pooled inventory center. Numerical results show that if customer demand distribution for products is normal, average inventory in centralized distribution system is less than that of decentralized distribution systems. Finally, sensitivity analyses are numerically conducted to investigate critical inventory parameters on service level of the local company.

One of the most issues of governments is to procuring food properly. Wheat and its products have strategic importance in consumable commodities basket and planning for its supply chain is one of the significant country’s needs. Also, wheat flour is one of the initial substances of many foods like bread, spaghetti, cookies, and confections. This paper proposed a multi-period, multi-product, bi-objective mixed integer linear programming minimizing the total cost and minimizing water consumption. Wheat supply chain network from farms, silos, flour factories, to customers is considered in this problem. This study aims to determine the wheat production amount, importing amount, and the quantity of water using of resources. Then, the bi-objective model converted to a single-objective one via the Weighted Goal programming method. Finally, the proposed model verified by a numerical example and results are presented. Also, the sensitivity analyses are shown to give a better insight and some suggestions for future works are presented.

By the rapid advancement of technology and the creation of global markets, competition, turbulence and environmental uncertainty have been enhanced. In the same vein, competition between companies has replaced the competition between the chains. Chaos and uncertainty have adverse effects on the supply chain and can lead to reduced corporate profitability and competitive advantage. In this situation, the selection of suppliers who can withstand more uncertainty and resilience and deliver the goods and services at the time specified by the customer is considered necessary for the organization. The purpose of this research is to evaluate the resilience of the supply chain in Mobarakeh Steel Co., Isfahan. To this end, the theoretical framework has first emerged from a comprehensive literature review and research on the resilience of the supply chain. With the help of this framework, the resiliency criteria of the supply chain were extracted and, according to experts, the criteria were confirmed. Then, using the DEMATEL method, the relationships between the indices and sub-indices were determined and using the ANP method, the importance of each of the criteria was determined. Among the criteria, the sub-criteria of agility, addiction, and risk management culture have the highest weight. At the end, they have been ranked by the Grey ARAS of the suppliers of Mobarakeh Steel Co. in terms of the degree of viability, and the supplier of Behran is considered at the highest rating.

One of the reasons for the high waiting time for patients in hospitals is the the lack of sufficient staff in the hospital, so the inefficiency of costs and job satisfaction of hospital nursing staff stems from the use of traditional and unscientific methods in allocating nurses to shifts. The present study is designed to determine the minimum number of nurse required according to the number of patients referred at different times, determine the shift schedule with the least required hours and schedule shifts for nurses in each shift with the lowest cost for the emergency department. The research method of the present study is of the mathematical modeling and research community, patients referring to the emergency department and nurses of a medical center. Data analysis is a combination of predictive methods, queuing theory models, and linear numerical programming. To predict the number of patients referring to the emergency, the time series method and ARIMA tools were used, and the M/M/C/K model was used to examine the queue system with limited capacity. One of the most important results of this study is to determine the maximum number of nurses available in each shift. Another result of this study is the comparison of the performance of each of the meta-heuristic Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Bee Algorithm (BA) with respect to the defined indicators.

The Corona Virus Crisis, which has plagued many countries for months, will change the world forever. The disease has disrupted markets, just as it has wiped out people. It will also change the political, economic and military power of countries forever. The consequences of the coronavirus are becoming more widespread, as well as affecting the military and causing governments to reconsider their defense and military policies. Given the priority of health care, it seems that the budgets of other sectors, including the defense sector, will be adjusted and reduced. This reduction will have a negative impact on the defense supply chain. This report tries to examine the impact of this disease on the defense supply chain; accordingly, the impact of this disease on the budget and defense credits, defense trade, and transnational defense projects has been expressed. Then there are the shocks of Corona's disease on production methods and the supply chain, the decline in demand for military products due to the spread of Corona, the impact on the defense industry, and finally the scenarios facing the defense industry to deal with the crisis.