Supply chain management
Peiman Ghasemi; Hossein Hemmaty; Adel Pourghader Chobar; Mohamad Reza Heidari; Mahdi Keramati
Abstract
Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to ...
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Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to minimize the costs and the next is to maximize the reliability in order to deliver the goods timely to customer according to the probable time and time window. The proposed problem has two levels of distribution. The first level, which is called transportation level, points to the distribution of products from a factory to an open distribution center, and the latter is known as routing level, which is related to a part of the problem in which we deliver products from the warehouse to customers. The proposed mathematical model is solved by Epsilon-constraint and NSGA-II approaches in small and medium, and large scales problem, respectively. The present study has provided the following contributions: concurrent locating and routing in the supply chain in accordance with the customer’s time window, probable travel time in the supply chain and customer’s reliability in the supply chain. The assessment metric results indicate the proper performance of our proposed model.
Supply chain management
Meysam Donyavi Rad; Ehsan Sadeh; Zeinolabedin Amini Sabegh; Reza Ehtesham Rasi
Abstract
The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management ...
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The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management cycle will reduce potential damage at the time of the disaster and reduce the vulnerability of society. Therefore, in this research, a mathematical model of crisis logistics planning considering the problem of primary and secondary crisis in disaster relief is introduced, which is the innovation of this research. In the primary crisis, the goal is to provide services and relief goods to crisis areas, and in the second stage, the secondary crisis that occurs after the primary crisis seeks to provide relief to crisis centers and transfer the injured to relief centers. Therefore, this research proposes a mathematical fuzzy ideal programming model in two primary and secondary crises. In the primary crisis, the goal is to provide services and relief goods to crisis-stricken areas. The secondary crisis, which occurs after the primary crisis, aims to support crisis-stricken centers and move injured people to relief bases in the second step. According to the proposed model, Bertsimas-Sim’s fuzzy programming that formulation proposed by Bertsimas and Sim [1] and robust approach we initially used. The Epsilon constraint method was used to solve the low-dimensional model. Multi-objective meta-heuristic algorithms have been designed to handle the computational complexity of large-scale real-time problems. Multiple comparisons and analyses have been proposed to assess the performance of the model and problem-solving capabilities. The results indicate that the proposed approach can be applied and implemented to develop a real-world humanitarian logistics network.
Decision analysis and methods
Niloofar Khalili; Parisa Shahnazari Shahrezaei; Amir Gholm Abri
Abstract
The current study, according to ergonomic factors, aims to model the nurses’ work shift scheduling problem. Considering the urgent needs of the hospitals in providing better services to patients, it seems significant to take the preferences of nurses in scheduling shifts into account. Therefore, ...
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The current study, according to ergonomic factors, aims to model the nurses’ work shift scheduling problem. Considering the urgent needs of the hospitals in providing better services to patients, it seems significant to take the preferences of nurses in scheduling shifts into account. Therefore, in this paper, a multi-objective model of nurses’ scheduling with emphasis on reducing their fatigue during the career shift is presented. To evaluate the outputs of the model, two numerical instances in small and large sizes with real data of Labbafinejad Hospital were designed in 18-person and 90-person wards. To solve a small size problem, a comprehensive standard decision method is employed, the results of which showed that nurses take their most rest during the night shift and in the middle of their working hours to reduce fatigue. Furthermore, due to the NP-Hard nature of the nurses' scheduling problem, in the problem of the 90-person ward, MOPSO and NSGA II algorithms are applied based on the design of a new chromosome. Using the TOPSIS method and entropy weighting method shows that the designed NSGA II algorithm can solve the nurses’ scheduling problem of Labbafinejad Hospital faster and better.
