جانمايي تجهيزات با تسهيلات متحرك در يك شبكه با در نظر گرفتن ملاحظات پدافند غيرعامل

LOCATING EQUIPMENT BY MOBILE FACILITIES IN CONNECTED NETWORKS CONSIDERING THE PASSIVE DEFENCE EXPLANATION

متحرك‌سازي تسهيلات كه يكي از اصول مكان‌يابي در پدافند غير‌ عامل است از مسايل نوين مطرح‏شده در مكان‌يابي مطرح شده است. در اين نوشتار دو مدل براي كمينه‌كردن جابه‌جايي‌ها در شبكه‌يي پيوسته از مشتريان و تسهيلات متحرك طراحي و توسعه داده شده است. در هر دو مدل ضمن تعريف متغيرهاي بيان‌گرِ تحرك تسهيلات و مشتريان، پارامتر تقاضا براي هر‏يك از مشتريان، و پارامتر ظرفيت براي تسهيلات شبكه در نظر گرفته شده است. در مدل دوم پارامتر وزن (اهميت) افزوده شده است. مدل‌هاي ارايه‏شده با استفاده از نرم‌افزار GAMS اعتبارسنجي شده، سپس مثال‌هاي عددي و ترسيمي از آن‌ها معرفي شده است. نوآوري مدل دوم (توسعه مدل اول) نسبت به مسايل كلاسيك متحرك، وابستگي حل مدل به حركت نقاط بدون در نظر گرفتن متغير زمان است .

In general, moving issues achieve an overall purpose in a network by the use of coordinate movements of a collection of objects. Since, today, technological progress is so fast, access to activities that are concerned with parameters, such as ways of saving cost, time, and displacement, require a definition for customers, to facilitate moving variables and restrictions in the network to achieve the networks purpose. This study developed a model aiming to minimize movement in locating mobile facilities and to provide service for high-priority clients in a given network composed of clients and mobile facilities, bearing two parameters in mind: the capacity of facilities and client priority. The validity of the model was then put to test applying GAMS software, and, thereafter, two numerical and graphical instances were introduced. Moving issues of mobility facilities is a new issue that has been raised in location finding. In this study, two models are designed and developed in order to minimize movement in a continuous network of customers and mobile facilities. In the presented models, the purposes are found with regard to some of the limitations in the network, such as capacity of each facility, and the importance and weight of each customer. In the first model, after defining variables that determine mobility facilities and customers, and considering request parameters for each customer, the parameter as a network facility capacity has been considered. Then, in order to define this parameter, limitation has been considered, which is obliged to not exceed the total facility capacity of total customer demand. The second model is designed considering parameters and variables as the previous model. Moreover, we find important parameters or weights of each network customer with the aim to serve customers with higher priority, in addition to minimizing movement. Then, the presented models have been validated and analyzed by the use of GAMS software. The number of network nodes, customer demand, facility capacity and node distance from each other are the parameters which the model has analyzed on the basis of their change. The innovation of the second model (development of first model) in comparison with Mobile Classical Problems is that solving the model contributes to the movement of points (vertexes), without any consideration of the time variable. The results found after analyzing the presented models are an increase in problem solving time with an increase in the number of nodes in both model, and the solvability of the second model because of the number of nodes being more than the first model, due to a virtual node.