supply chain management analyzing/modelling
Behzad Masoomi; Hassanali Aghajani; Ahmad Jafarnejad; mohammadmehdi movahedi
Abstract
Purpose: The aim of this research is to optimize humanitarian logistics to increase coordination between actors in the phase during and after the disaster and aims to minimize the cost of relief, minimize the time of relief and minimize the cost of rebuilding infrastructure and housing for the affected ...
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Purpose: The aim of this research is to optimize humanitarian logistics to increase coordination between actors in the phase during and after the disaster and aims to minimize the cost of relief, minimize the time of relief and minimize the cost of rebuilding infrastructure and housing for the affected people.Methodology: This research is a part of developmental research in terms of the research directions types ; Because it is trying to expand the existing models in the design of the humanitarian logistics network and consider the optimization of two phases during and post-disaster. The proposed model of this research has been solved using multi-objective genetic algorithm and multi-objective particle swarm.Findings: The implementation of this study will lead to a reduction in the costs of locating, routing and reconstruction in the humanitarian supply chain, as well as reducing the time of providing aid to the affected people and increasing their satisfaction. It is also possible to reduce the inventory of relief products with the help of this issue. Appropriate planning in humanitarian logistics processes, especially in the coordination phase of reconstruction, will be done according to the limited budget of governments and the appropriate use of resources.Originality/Value: One of the innovations of this study is reducing the cost of reconstruction after an earthquake. Several studies were conducted in order to recover from the disaster. Over the past two decades, response phase relief operations have been the focus of a significant number of researchers. However, the issue of post-disaster recovery and reconstruction programs has not been sufficiently discussed in scientific and practical forums.
Optimization in science and engineering
Nazila Adabavazeh; Mehrdad Nikbakht; Reza Tavakkoli-Moghaddam
Abstract
Purpose: Extent of an application and importance of a welding industry and economic opportunities of this industry need to develop appropriate strategies to pave the way for the economic growth as a strategic industry with sustainable competitive advantage. The high cost of the gas tungsten arc welding ...
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Purpose: Extent of an application and importance of a welding industry and economic opportunities of this industry need to develop appropriate strategies to pave the way for the economic growth as a strategic industry with sustainable competitive advantage. The high cost of the gas tungsten arc welding (GTAW) process in a welding industry due to the advantages of excellent welding quality and low complexity of this process requires management. Therefore, careful study and evaluation in the correct use of the GTAW process with financial resources seems to be very necessary. Modeling leads to efficient decision making along with competitive advantage in strategic planning. Today, by planning, sustainability goals and considerations can also be achieved in addition to achieving economic goals.Methodology: In this study, a linear programming model for the problem of minimizing the cost of the GTAW process according to different automatic or manual conditions is presented by a skilled welding operator. GAMS software is used to solve the problem and validate the proposed model. Finally, to evaluate the applicability of the model, four scenarios of the case study are solved and explained as well as sensitivity analysis.Findings: The results show that from an economic point of view, the proposed model can reduce costs and increase efficiency and customer satisfaction. The proposed approach leads to the improvement of the shielded tungsten arc welding process and the increase of management insight.Originality/Value: Mathematical cost modeling can provide a comprehensive analysis of management decisions. The cost minimization model helps managers to understand the cost structure and behavior. Considering the scope of welding application, minimizing the costs of this activity will lead to a reduction in the total cost of an industry
stochastic/Probabilistic/fuzzy/dynamic modeling
Mohamad Sharifzadegan; Tahmourth Sohrabi; Ahmad Jafarnejad Chaghoshi,
Abstract
Purpose: The complex conditions prevailing in the industries and the increasing costs of production equipment and machinery and competitiveness in gaining market share, show the role and importance of production planning and maintenance with other parts of the industry. Integrating such decisions can ...
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Purpose: The complex conditions prevailing in the industries and the increasing costs of production equipment and machinery and competitiveness in gaining market share, show the role and importance of production planning and maintenance with other parts of the industry. Integrating such decisions can take fundamental steps to reduce costs and increase quality. Maintaining and creating the continuity of production activities depends on accurate and correct planning of production, maintenance activities and how to support these processes. The need for integration and coherence in the simultaneous planning of such activities causes a lack of rework and parallel work and obstacles and delays and inconsistencies at different levels of production.Methodology: In this research, a two-objective mathematical model of production planning and repairs with limited resources is presented in conditions of uncertainty.Findings: The results of comparing accurate and meta-innovative solutions show the improvement in the company's products and the optimal use of material and human resources. Sensitivity analysis also shows that the failure rate of the machine before and after preventive maintenance has a great impact on the value of the objective function of the mathematical model. The results show that the average error of the ant algorithm is only 3%. This is while the average solving time in GAMZ is 45,000 seconds, while the average solving time of the ant algorithm is about 354 seconds.Originality/Value: This shows that the ant algorithm has a very small amount of error with much less time and therefore the efficiency of this solution method can be well explained.
Optimization in science and engineering
Mohammad Namakshenas; Mohammad Mahdavi Mazdeh
Abstract
Purpose: The chemical attributes of Technetium-99m have made it popular for most medical imaging procedures. However, in recent years, the decay product of molybdenum-99, i.e., technetium-99m, has become expensive, and its routine availability can no longer be taken for granted. We proposed scenarios ...
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Purpose: The chemical attributes of Technetium-99m have made it popular for most medical imaging procedures. However, in recent years, the decay product of molybdenum-99, i.e., technetium-99m, has become expensive, and its routine availability can no longer be taken for granted. We proposed scenarios to maximize the throughput of Technetium-99m which is used to produce radiopharmaceuticals in a medical imaging center.Methodology: We proved a recursive function to imitate the decay dynamics of Technetium-99m, which is used in 80 percent of medical imaging. Then, we proved necessary and sufficient optimality analysis for this function.Findings: We found optimal scenarios for distributing the radiopharmaceuticals into elusion periods according to clinical considerations.Originality/Value: We developed a rigorous mathematical model based to maximize the throughput of radiopharmaceuticals in a molecular imaging center.