فصلنامه مدیریت زنجیره تامین
پیاپی 66 (بهار 1399)

The purpose of this research is to design and optimization the supply chain network under disruption conditions with considering to location- routing problem. For this purpose, a four-echelon network was considered including supply, production and distribution levels and customers where the raw materials were purchased from suppliers and sent to the producers. Then products are manufactured by the producers sent to distribution centers in order to be delivered to customers by optimal routing. Sometimes disruption is exerted in this network by customers or suppliers or both and this will lead to change in demand or capacity. At the end, the nonlinear planning integrated model is formulated and the relationship between the components of the chain and the number of facilities was examined. To this end, a scenario-based approach was used to control the disruption and the conditions were examined in 3 scenarios, using these scenarios, the least disruption was identified. Also, by using this model, it is possible to determine the potential location for production and distribution centers and determined the optimal route of communication with supply and production and distribution centers, the customer. Model with Use of the problem designed by the simulation algorithm, In Gams software is implemented and by using scenarios to reduction and increase demand Sensitivity analysis. The results confirm the effectiveness of the suggested model.

The conditions of the business environment of the manufacturing units and the multitude of factors affecting their performance have always emphasized the need for planning as one of the main tasks of management. In this regard, production planning in manufacturing companies is one of the most important tools for success. This paper attempts to present a comprehensive model for production planning in the industry using appropriate operations research -based techniques so that a suitable model of rational communication between operations can be formulated and so that decision makers can better plan and increases productivity. In this paper, after a brief introduction about one of the products of Ekbatan Gas Control Company, the production planning of this company will be carried out with the objective of cost reduction, demand satisfy minimizing surplus inventory in discrete production systems. In this study we intend to apply all parameters and variables of production in a comprehensive model, considering the production method of Ekbatan Gas Control Company. In the proposed goal programming model, simultaneously different and contradictory objective functions of the company have been considered. The approach proposed in this study increases the company's profit 3%. Also production of first product increases18% and the second increase 3%. It has also increased production capacity, and it satisfies 100% of the demand. The results of the model show a significant reduction in overtime, and only in the fourth period need to overtime for produce the first product. As consequences it eliminates the need for hiring and layoffs, and reduces their cost to 0. In fact, the Company will have a significant increase in number of production and profit with the samee number of manpower. The proposed model is expected to serve as a reference for future planning of the firm's corporate policies.

Under no circumstances, the importance of health supply chain management can't be diminished. Locating health centers and hospitals in natural disaster scenarios can lead to greater control over life and financial losses. In this paper, three main levels, such as demand points (cities of Guilan province), health centers/hospitals and suppliers are defined to locate the mentioned facilities, which have been solved using linear and deterministic planning model. The optimization model approach and the final solution are solved and presented accurately considering Guilan province. The main purpose of this proposed model is to minimize construction and relocation costs due to disruption in hospitals, health care centers, especially links between demand points and hospital/medical centers, as well as between suppliers and hospital/medical centers.

In this research, a real and practical problem of the distribution system of a car parts manufacturer is modeled. Qafliran Company, which is one of the leading manufacturers in the field of parts manufacturing for automakers and retail market, has produced various products and tries to get the highest customer satisfaction in timely delivery at the lowest cost in its distribution system. In this research, a model of vehicle routing is presented in which the time window and the multi-product demand of customers are considered in fuzzy mode. Each customer has a trapezoidal time window to receive orders in which customer satisfaction is at best 1 and decreases before and after of expected time of the customer. The objective function is to minimize the distance traveled by vehicles and maximize customer satisfaction. The proposed model was solved by GAMS software and the results showed a very good improvement compared to the current company performance.

In recent years, the increasing pollution of the environment and its destructive consequences, as well as the growing concern about it, has led to new concepts and approaches to reduce these effects and preventive environmental measures. One of the most important of these approaches is the green supply chain. Green supply chain integrates supply chain management with environmental requirements in all stages of product design, selection and supply of raw materials, production and manufacturing, distribution and transfer processes, delivery to customer and finally after consumption, recycling management and Re-consumption is designed to maximize energy efficiency and resources while improving the overall performance of the supply chain. In this paper presents a multi-objective model for a green supply chain network. To solve it, the LP-metric method is used, which is coded in Gams software. The results show that the study of two important factors of cost and carbon dioxide emissions, as one of the most important and well-known pollutants, has led to the application of this model in the supply network and. The results also show that it is more important to pay attention to greenhouse gas emissions at higher demand.

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.