فصلنامه مدیریت زنجیره تامین
پیاپی 67 (تابستان 1399)

Many researchers have simultaneously investigated location and inventory decisions. Furthermore, environmental factors in the design of supply chain networks have been studied. In this paper, a mixed-integer nonlinear programming model for the forward / reverse location-inventory problem with limited capacity considering production, distribution and recycling chain of automotive tires as a case study has been proposed. Compared to the previous research, a number of distribution centers, inspiring the real world situations, between factories and demand markets are considered and inventory decisions in those centers are also integrated in the model. Furthermore, the model in the uncertainty situation of key parameters such as demand and rate of return of products have been examined and analyzed. For more comprehensiveness of the model, environmental factors are considered in order to make the model closer to the real world situations. The developed model is investigated and analyzed utilizing different methods of multi-objective programming techniques.

One of the main challenges of the governments of each country is the increase in pollution caused by the production of products by manufacturers. Increased pollution leads to a significant growth in the number of patients with heart failure, respiratory failure and other diseases. One of the ways to deal with this situation is to produce green products with the least degree of pollution caused by the production. The green supply chain is one of the necessary solutions to improve the current situation. Pollution is not only due to the production of the product by the manufacturers, but also the transportation of products by non-standard means of transport is a factor in the production of pollution. In this study, a supply chain with a manufacturer and a third-party logistics company (3PL) that the government monitors the supply chain is considered. The government monitors on the supply chain by setting tariffs for the producer. The results show that the presence of a 3PL, although it increases the selling price of products, but reduces pollution and also increases the amount of demand.

One of the issues facing urban communities is waste management. In this paper, we determine the location of landfills, the capacity of these sites, the location of transfer stations, their capacity, and the location of waste recycling centers in such a way that the total costs (including the costs of establishment and transportation of waste from production to refining sites, landfills and recycling centers) are minimized. We also control pollution levels by defining a maximum allowable pollution for each population center to comply with environmental constraints. In this study, the problem is formulated as a mixed integer programming model. Then, the capacity of the landfill and the capacity of the refining sites are considered as uncertain parameters and a robust optimization model is developed. Also, to validate the model, a problem instance is solved and the computational results are presented for different levels of conservatism. The decision maker can use the results to select the appropriate level of conservatism.

In the present era, organizations and companies are seeking to take sustainability measures into their core functions. One of these measures is the assessment of suppliers based on sustainability indicators. Also, organizations must have sufficient knowledge and information about their field of work and sustainable development so that they can take steps to implement sustainability measures. For this purpose, knowledge management is one of the most important factors that has a significant impact on the implementation of the sustainable supply chain. Since knowledge management plays an important role in advancing the goals of the successful organizations of the world, it can be said that knowledge management can be used to achieve the sustainability of the supply chain. The purpose of the present study is to analyze the role of knowledge management in sustainable supply chain management with interpretive structural modeling approach. For this purpose, after studying the literature of research and interviewing experts, 19 factors have been identified that affect the implementation of knowledge management in sustainable supply chain management. These factors were then formulated in the form of an ISM questionnaire and distributed among the experts. After analyzing the data and designing a structural model for the factors affecting the implementation of knowledge management in the sustainable supply chain, a total of 19 variables were identified in 12 levels. In the analysis of Micmac, the independent and dependent variables and binding variables, which have a two-way relationship with other factors, were also identified.

Emergency Medical Service (EMS) Systems provide pre-hospital emergency care services to patients and injured. Needed time in order to respond to an emergency call (arrival time to the scene of the accident) is one of the most important aspects of EMS service facility. Optimal planning of resources for rapid response has been made difficult due to the random number of ambulance requests and operational constraints. This difficulty is particularly important in the dispatching and allocation of ambulances in the urban area. In the present study, simulation modeling has been used to plan the dispatching and allocation of ambulances in the urban area. In order to achieve rapid response, the modeling prioritizes emergency calls to cover specific patients, such as heart patients, in the shortest possible time. The study has used ED simulation software for dispatching modeling of emergency servers at a city level with different demand points and random distribution functions for demand and service rate of servers. In this regard, two scenarios have been developed that have been repeated to the required number and then compared using statistical methods according to performance criteria such as patients' probability of survival, mean response time and service time. In this study, the best-case scenario is that by deploying a variable server at each base in order to response emergency, it improves responsiveness and performance measures.

Production and Distribution planning of radiopharmaceutical products aroused as a major concern due to the increasing the number of cancer patients and deaths. Radiopharmaceuticals are not only used for diagnosing process but also utilized for evaluating the function of body tissue and treatment. Shorter half-life of the radiopharmaceutical products rather than deteriorated products have complicated its production and distribution decision problems. In this paper an integrated mathematical programming has been developed for optimizing production, distribution, and injection planning of the radiopharmaceutical products. The proposed model aims to maximize production profitability through decreasing the production costs. Also the trade-off between production cost (depend on the time it takes to bombard raw materials) and the deviation time between production and injection times have been considered according to the nature of radiopharmaceutical production process in real-world problems. Furthermore an injection time window is considered for customer shown the preference of the customer to receive the radiopharmaceutical. The validity and efficiency of the proposed model were analyzed by implementation in a case study. The results show that the integrated model of production and distribution planning can not only decrease the cost of production but also increase the satisfaction level of the customers.