Geographic Information System (GIS)
Hossein Etemadfard; Hamed Kharaghani; Mahdi Najjarian; Rouzbeh Shad
Abstract
Extended AbstractIntroduction:The increasing demand for sustainable food consumption as well as the change in the consumption pattern has led to efforts to improve the food distribution process. This is to speed up service delivery and prevent the spoilage of perishable materials. Among the most significant ...
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Extended AbstractIntroduction:The increasing demand for sustainable food consumption as well as the change in the consumption pattern has led to efforts to improve the food distribution process. This is to speed up service delivery and prevent the spoilage of perishable materials. Among the most significant topics in the food supply chain is perishability, a phenomenon that occurs in certain categories of products such as fruits, vegetables, and dairy products. Perishability refers to the property in which a product loses its commercial value and usability after a certain period. However, meeting the general needs of citizens, especially the supply of food, is one of the most significant axes of urban service activities on the city's economic platform. In addition, the provision of comfort and well-being for residents depends on the proper establishment, optimal distribution, and sufficient variety of products offered in shopping centers. Day markets as well as fruit and vegetable fields provide fast and appropriate daily needs for residents. In addition, choosing fast and reliable routes for food distribution in the city is one of the other significant and influential factors in providing quality services. It should also be noted that in vehicle routing problems (VRP) related to food products, routes for vehicles must be created that match the schedules of some stores to deliver products.Materials and Methods:To optimize the fruit and vegetable distribution routes between the fruit and vegetable fields and Shahre-ma stores in Mashhad, this research will use genetic algorithms and particle swarm algorithms. This research will have the aim of optimizing distribution time, which was not addressed in previous research. This research presents its innovation by considering a three-hour time limit in the problem-solving algorithm. Genetic Algorithm (GA) is a learning method based on biological evolution and influenced by the hypothesized mechanism of natural selection in which the fittest individuals in a generation survive longer and produce a new generation. And in this article, it is implemented in such a way that the algorithm itself determines the most appropriate number of vehicles. The number of vehicles should be such that distribution among all stores is done in less than three hours and five minutes in each store. There should be a stop. And if distribution among all stores is not done in less than 3 hours, a new vehicle will be added to the number of vehicles. Also, particle swarm optimization (PSO) is a technique inspired by the behavior of birds when searching for food. In this research, the data collected include the location of Shahre-ma stores and the fruit and vegetable square in Mashhad city. These data were prepared from the information of Mashhad municipality. Also, to implement these algorithms, MATLAB software has been used. Network analysis has been done to determine the distance between Bar Square and Shahre-ma stores in ArcGIS software using network analysis.Results and discussion:This research proposes several hypotheses, including that the maximum optimal time is 3 hours and products should be distributed by 7 am in all places. Also, city traffic is uniform from 4 to 7 in the morning and the same product package is distributed in all stores. Comparing the results of two genetic algorithms and particle swarm shows that the genetic algorithm has a higher efficiency in optimizing the distribution path of fruits and vegetables. Because the time of the four routes derived from the genetic algorithm is approximately 92 minutes, 84 minutes, 80 minutes, and 82 minutes respectively. The total length of all routes is 127 km and 779 meters and the total time of all routes is 338 minutes. And the time of the four routes obtained from the particle swarm algorithm is approximately 102 minutes, 103 minutes, 89 minutes, and 91 minutes respectively. The total length of all routes is 175 km and 390 meters and the total time of all routes is 385 minutes. And in total, the times obtained for four vehicles in the genetic algorithm were 47 minutes less than the particle swarm algorithm. In addition, the total length of the paths in the genetic algorithm was 47 km and 611 meters less than the particle swarm algorithm.ConclusionThe genetic algorithm was able to achieve the optimal solution by evaluating the objective function 12,000 times. This is 2,900,000 in the particle swarm algorithm. Accordingly, the time required to reach the optimal solution differs significantly between the two algorithms.
Mehrdad AhangarCani; Mohammad Reza Malek
Abstract
Extended Abstract
Introduction and Objective
Road traffic accidents impose numerous social, economic, and cultural costs upon various societies, especially developing countries. Identification of accident blackspots is a method proposed to deal with car accident risks. Among various events associated ...
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Extended Abstract
Introduction and Objective
Road traffic accidents impose numerous social, economic, and cultural costs upon various societies, especially developing countries. Identification of accident blackspots is a method proposed to deal with car accident risks. Among various events associated with transportation network, road traffic accidents play a significant role, because of their specific features, including high frequency, high intensity and the chance of direct involvement of all members of the community.This problem is more conspicuous in developing countries such as Iran. The present study aims to identifyaccidentblackspotsand to prepare risk map for road trafficaccidents in Babol city using volunteered geographic information.
Materials and methods
According to the characteristics of the study area, the present study takes advantage of criteria such as distance from population centers, proximity to city squares, distance from footbridges, and proximity to road intersections to identifyaccidentblackspotsand a prepare risk map for roadtraffic accidents in Babol city. Accident blackspots detected by volunteered geographic information, along with the criteria determined by applying analytic hierarchy process (AHP) and analytic network process (ANP) were compared in a pairwise manner, and their respective weight was calculated to showtheir specific level of impact. Ultimately, a risk map was produced for the risk of road traffic accidents obtained from each method. In order to evaluate the accuracy of the identified accident blackspots obtained from volunteered geographic information, as well as the accuracy of susceptibility maps, ROC curve and Kappa Coefficient were applied to police official records.
Results and Discussion
According to the findings, Jame Mosque shopping center, Shahabnia shopping center, intersection of Farhangstreet and Velayat square were identified as the most accident-prone areas in Babol city. Also, among the prespecified criteria, distance from population centers and distance from intersections are considered to be the most important criteria, respectively. Results obtained from the evaluation criteria indicatedhigh accuracy of volunteered geographic information, and thus it is concluded that this kind of information can be effective in determining the accident blackspotsinBabol city. Also, the ANP method works better than AHP method in preparing the risk map of accidents.
Conclusion and Future works
Due to the large number of road accidents, especially in developing countries,the issue of accident blackspotsand providing a risk map for road trafficaccidents are an essential part of roads safety. In the present study, volunteered geographic information was used, along with multivariate decision-making methods of analytic hierarchy process (AHP) and analytic network process (ANP) to identifyaccident blackspots based on number, causes and severity of accidents and to develop a risk map for driving accidents in Babol city. Moreover, the criteria of distance from population centers, proximity to the city squares, distance from the footbridges, and adjacency to intersections were used to determine accident blackspotsand to prepare a risk map for driving accidents in Babol city. According to the results, Jame Mosque shopping center, Shahabnia shopping center, Farhang intersection and Velayat square were identified as the most accident-prone points in Babol city. Also, distance from population centers and distance from intersectionswere identified as the most important criteria, respectively. Evaluation criteria demonstrated that volunteered geographic information can be effective and accurate in determining accident blackspotsinBabol city. Also, the ANP method worked better than AHP method in preparing the risk map of driving accidents. The method proposed in this study to identify accident blackspots and preparedriving accidents risk maps can be generalized to other areas. Basedon the characteristics of specific routes, other criteria such as arc radius, longitudinal slope can alsobe used. It is also suggested that the results of other methods used for investigation ofaccidentblackspotsand production of risk maps based onvolunteered geographic information (VGI) are compared with the results of the present study.
Meisam Rostami; Ramin Kiamehr; Ramin Bayat
Abstract
Considering theproper and comprehensive criteria at the route locating stage can play a major role in reducing economiccosts, increasing safety and accessibility to roads and preserving the environment. For this purpose,several parameters such as Ground Elevation Model, land cover, demographic and tourism ...
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Considering theproper and comprehensive criteria at the route locating stage can play a major role in reducing economiccosts, increasing safety and accessibility to roads and preserving the environment. For this purpose,several parameters such as Ground Elevation Model, land cover, demographic and tourism information, how sunny the roads are during cold seasons, distribution of rivers and fault lines were considered for optimal routing of the Ilam-Homeil road in this research. In order to determine the inter-layer cost, a knowledge-based approach was proposed based on which, a cost function was considered for each of the layers in accordance with its characteristics and its way of influence on providing the goal. The main advantage of this approach isthat the cost variations are not merely linear for the existing data intervals in each one of the layers, and the characteristics of corresponding layer areincluded in the definition of relevant cost function. Next, the pair-wise comparison and Analytical Hierarchy Process (AHP) wereused, taking advantage of the experts’ opinions, for inter-layer weighting. Accordingly, the shortest routewas implemented throughcombining layers and the method of overlapping index by providing the lowest cost with 3 variables or different variants. In the first variant, the common methods (linearly) were used for inter-layer weighting. In the second variant, the only criterion used for determining the route was the slope criterion. The proposed method of knowledge-based weighting was applied in the third variant, taking into account all the criteria. Based on the results, less attention has been paid to factors such as distance from the fault lines and the rivers, access to population centers and tourist area in determining the constructed route, and the main criterion in routing has been the topography of the region alone. Also, the length of the route in all of the three variants is less than the length of the constructed route. In general, the route resulted from the application of knowledge-based weighting has a better statusin providing different criteria than the constructed route, as well as the two other variants.
Mahdi Modiri; Reza Aghataher; Mohammad Fallah Zazuli; Mohsen Jafari
Volume 22, Issue 86 , June 2013, , Pages 5-16
Abstract
Effective planning and decision-making require access to accurate and updated information. Having updated spatial information and proper application of it is one of the most important topics in the command. A C4I system is composed of several smaller systems that can help military commanders assess the ...
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Effective planning and decision-making require access to accurate and updated information. Having updated spatial information and proper application of it is one of the most important topics in the command. A C4I system is composed of several smaller systems that can help military commanders assess the enemy’s information and make better decisions. Geospatial Information System )GIS( can assist commanders in achieving more rational decisions. GIS by modeling the Earth and the effect on Earth will provide a good view of the operating area for military commanders. This article reviews the role and application of Geospatial Information System in development of command and control.Using of new technologies such as mobile Geospatial Information System )Mobile GIS( and web-based Geospatial Information System )WEB GIS(, followed by locating the best places with different functions are GIS capabilities in command and control )C4I(.Thus, using Geospatial Information System capabilities by modeling of the operating area can be reached the highest rates in optimal and valid decisions for command and control.
