جواد صابریان

With the growth of urbanization, urban transportation has become one of the most critical challenges of urban management, which is closely related to the economic power of cities and countries. A robust economy requires adequate infrastructure in the freight division, and proper resource planning and management is the key to its success. In this research, the issue of transportation of postal items has been considered. The use of traditional methods prolongs receiving and delivering postal items and thus increases its costs. In this research, this issue has been studied. Using meta-heuristic algorithms (Artificial Intelligence), an attempt has been made to optimize the problem of receiving and delivering postal items.

The proposed method of this research is based on the use of a Genetic Algorithm to optimize the order of pickup and delivery of postal items using the travel cost matrix between the points of pickup and delivery. The genetic algorithm has high flexibility following the structure of different problems. In the developed model of this research, the order of picking and delivering shipments in each freight vehicle is in one array and five arrays representing five freight vehicles from five postal centers in one matrix created. The genetic algorithm tries to optimize the final solution by randomly generating these matrices (chromosomes) and measuring the fitness function of each matrix (answer) and using the combination and mutation operators. Finally, the best solution is obtained, which is the best arrangement and planning for the trucks carrying the items, in which the best order of receiving and delivering the postal items is determined.

The study area is 10, 11, 12, 14, 15, 16, 17, and 19 regions of Tehran (the capital of Iran), which were selected for implementation. Street network data was entered into the Network Analyst tool in ArcGIS software. Travel cost matrices between pickup and delivery points and consignment centers were extracted from the data of 50 pickup points and 50 delivery points entered into the developed model. After executing the algorithm for 1000 times and generating final output, which is the most optimal arrangement of pickup and delivery points, it was compared with the first random answer made in the model which represents old unplanned method for receiving and delivering the postal items. The total length of final optimal answer is 551689 meters, which is less than 720287 meters (the total length of first random answer). The decrease in the final solution in comparison to the first random solution is 168598 meters, which is equivalent to 24% savings and indicates the efficiency of the developed model.

Using old traditional experimental methods for pick-up and delivery of postal items leads to increase the route of postal vehicles which increase the urban congestion and produces some pollutions. Applying the scientific methods such as used model in this research helps to decrease the aforementioned problems and it is a key to approach the smart cities. We used a genetic algorithm optimization method for arranging the order of receiving and delivering the postal items and develop a method to decrease the distance between request points. By using this algorithm, the total length of postal vehicles decreased from 720 km to 551 km which is equivalent to 24% savings.For instance, the second truck's way can be checked to investigate the proposed model's performance. Since can be observed, the algorithm has put the pick-up and delivery points together properly to stop the truck from driving around the study area. It can similarly be recognized that the truck's movement numbers are adjacent to each other. It means that the delivery points are ordered to follow each other, and the postal vehicle evades moving significant ways. Consequently, the vehicle's driving length is decreased, which decreases the overall driving length of all vehicles. Nevertheless, the first vehicle's route does not look so visually optimal. It can be seen that the vehicle has been required to move to some distant points. First, the ultimate solution's fitness function's state holds the lowest possible value among the solutions. Furthermore, the algorithm could not optimize the paths more, and it has to insert some distant locations in the route of one of the vehicles. Indeed, every attempt has been performed to gain the most suitable paths. However, we can optimize this problem by improving our methods or use other metaheuristics algorithms for future research.

The oil sector has served as the predominant catalyst of our nation's economy since the oil industry was nationalized in Iran. Oil facilities are integral to the oil industry, and among the most crucial facilities throughout the nation are pipelines. The extensive network of pipelines, which facilitate the transportation of oil from production sites to the country's refineries, as well as the distribution of refined products to consumption centers, represent vital economic and industrial lifelines. The spatial challenge lies in the intersection points of these pipelines, which can be effectively addressed through the use of geographic information systems. The accurate and optimal routing of pipelines is of utmost significance and should be executed in a manner that aligns with technical and economic ideals, while minimizing adverse societal and environmental impacts.

In this research, an attempt has been made to ascertain the routing of the multi-directional pipeline by taking into account a plethora of criteria, data, and spatial and descriptive information. This information encompasses factors such as land slope, vegetation, water flow, faults, residential and population centers, power transmission lines, pipelines in the region, and roads, among others. Given the extensive range of indicators associated with the routing of energy transmission lines in existing research references and executive reports of projects, this article focuses on thoroughly examining and providing a specialized classification of these indicators. In the subsequent stage, Geographic Information System (GIS) is employed as a framework to integrate the diverse components of information. This integration allows for the utilization of varying influence weights during the compilation of indicators, based on the significance of each indicator's impact on the subject matter. For this purpose, the conventional fuzzy AHP method has been used.

The research conducted in this study focuses on the geographical area of Khuzestan province, specifically its northern region located between Rig Valley and Sabzab. The objective of this research is to establish the optimal route for the transmission line of oil, taking into account three different scenarios: economic optimality, environmental optimality, and a combination of both. The findings reveal that selecting the most favorable route in this context, in comparison to the current transmission line, leads to a reduction of 141 meters in terms of the economic scenario, 635 meters in terms of the environmental scenario, and 586 meters in terms of the comprehensive scenario. These outcomes represent tangible accomplishments resulting from the research.

The findings of this study clearly demonstrate that the conventional techniques for designing pipelines are insufficient in incorporating all the relevant criteria in the pipeline route design. Regardless, it is crucial to acknowledge that the quality of the routes produced with the aid of Geographic Information Systems (GIS) heavily relies on the quality of the input data. Any discrepancy or flaw in the input information may yield design outcomes that raise doubts about the effectiveness of the work. Consequently, in addition to harnessing the capabilities of GIS, meticulous attention to detail must be exercised during the data collection process. Another notable aspect of this research is its capacity to consider various scenarios. By leveraging this capability, decision-makers are empowered to make informed choices regarding the pipeline by examining the outcomes of diverse scenarios and taking into account a range of factors.

Today, it is very important to know the quantitative and qualitative characteristics of changes in environmental planning, land use and sustainable development. Currently, the use of vegetation maps is one of the important elements in generating information for macro and micro planning. In general, there are various methods for collecting data, including astronomical observations, photogrammetry, mapping and remote sensing. Remote sensing is one of the data collection methods in which it has the least amount of direct contact with the objects and features being measured and unlike other methods in which human factors play a role in collecting and interpreting terrestrial data, in remote sensing method the task of collecting information will be the responsibility of the sensors. Due to the over-exploitation of natural resources, the landscape is constantly changing and monitoring these changes as well as updating maps is costly and time consuming, so many developed countries now have to prepare maps in Different levels use satellite data.

In this research, we will how remote sensing satellite images can be used to prepare maps of vegetations. The use of plant coating maps is one of the important pillars in the production of information for macro planning. The aim of this research is to produce a map of natural and cultivated vegetation as well as irrigated lands and gardens using remote sensing technology and geographic information system. For this purpose, satellite images and ground surveys were used as input data and these data were analyzed using different methods of classification. As a case study the south of Zanjan city was selected for preparing of land use map. The Sentinel-2 satellite images of 2018 were used. Several software such as Envi, ArcGIS, and SAGAGIS were used. The best classification method was selected using ArcGIS software. To check the functionality and efficiency of the data, normalized vegetation index (NDVI) images were calculated with a spatial accuracy of 15 meters and one NDVI image was considered for each month. In total, 12 images are selected and converted into a triple band by layer stacking.

Data validation is based on Google Earth and the precision of the vegetation of the study area was studied using classification methods such as Maximum Likelihood, Minimum Distance, Support Vector Machine, Neural Network and Random Forest. In each classification method, the Kapa coefficient has been examined by using the commission and omission error matrix and the overall accuracy of the map. It was determined by comparing all the methods and evaluating the obtained results, Random Forest Algorithm method with overall accuracy of 96.51% and kappa coefficient of 0.8181 was chosen as the best method of vegetation classification in the study area.

The results of this research indicated that in the random forest algorithm, the probability of each pixel belonging to each class is determined with high accuracy. The ability to determine the importance of features in the classification that can be used to select the optimal feature space is one of the most important advantages of this method. Also, the ability to classify noisy data, which can be used to increase and refine training samples, no need to select or reduce bands when using multispectral images, are other advantages of the random forest algorithm. In this way, the simplicity and comprehensible structure of this algorithm, along with its technical advantages, has made it highly flexible and made it very easy to combine with other methods.

Today, travel sharing is a new approach to reduce traffic congestion and its problems, in which people travel with others on their journey, reducing traffic congestion by avoiding single-occupancy. Sharing either cars or taxies is one of the most interesting ways that it has been used in some countries recently. In this phenomenon, 2 or 3 people use other’s car or taxi. In this article, after studying previous researches on this topic and examining the theoretical foundations that include artificial intelligence algorithms, it was decided to apply Genetic Algorithm to align and arrange passengers to find a way for passengers to optimally fit together. The concept of network analysis has been used to calculate the cost of travel between origins and destinations for passengers. It is a novel method to share taxies that uses a delay time for each passenger at computations. Therefore, some taxis will be turned off and this helps to decrease urban traffic jam in cities. The results show that the proposed model turn off 69.8 % of taxies and also 27.8 % of them carry more than one passenger, so this proves the performance of the proposed model.

Due to the water shortage and drought that have occurred in recent years in our country, the planning for the optimal management of water use in different applications is necessary. The agricultural sector is the largest consumer of water and yet most of the water loss is also related to it. As it is said, about 60% of drinking water is wasted in agriculture.
Since irrigation is primarily a matter of spatial case, and is related to the location information such as the location and position of land, location of transmission canals and etc., so capabilities of spatial information systems (GIS) could be used for better and more successful planning.
In this paper, using optimization capabilities in GIS, program of irrigation of reservoir dams have been set, so that the farmer’s water need to be covered and the amount of waste water to be at least. For this purpose, the path of the water motion in the canals is minimized and the irrigation of farms that are under one canal be done simultaneously. If not enough water in the reservoir, Method of determining the optimum cropping pattern using the AHP method are provided. The method presented in this paper has been implemented and evaluated in a case study in Golestan dam irrigation network.

Nowadays, the problem of transportation and traffic has become a social challenge in many countries. With the advancement of science, a favorable environment for an intelligent and purposeful management is achieved in order to improve productivity and increase efficiency of network traffic. In the field of information technology, Geographic Information Systems are very important in optimizing the performance of transportation systems. In this context, the capabilities of network analysis in GISs such as shortest path computing could be very useful.
Different criterions have ever considered for shortest path analysis in GIS. Distance, travel time, path comfort, path beauty and etc., are some of these criterions. Travel time criteria has some random continues variations, because of its relation to traffic. Therefore, the travel time of each street must be calculated based on its geometric and traffic momentarily.
In this paper we have developed a model for this purpose that is based on wavelet transform and least square method. This model uses the statistical information of travel time in previous days for prediction of travel time in future. Finally for testing the developed model a case study have been explained in this paper.

Mobile devices are widely used and they are providing people with needed information anytime and anywhere. One of the most important mobile applications is related to the navigation and other GIS capabilities. The development of mobile applications needs to be adapted with the special features and limitations of this computing environment. Looking in this direction, we present a context aware mobile map representation which used the dual graph of street networks for automatic simplification and generalization of streets in various contexts. For this purpose, after the introduction and selection of context factors, the degree of dual graph nodes are used for automatic generation of maps with fewer details. We will show that we could increase the capability and efficiency of mobile GISs by using dual graphs, because by using that, the structure and the topology of street network could be maintained in generalization process. The proposed approach is validated by a case study applied to a region of Tehran city. The case study clearly showed the benefits of usingdual graphs in mobile map applications.

Geographic information systems to map the different situations require different details and different representations. For example¡ the map display to a user who is driving at high speed must be different from the user is standing or moving at low speeds. At higher speeds the lower scales with low details should be done to make the best map used by the user. Maps with different scales and different details must be done intelligently and automatically. In this research¡ in addition to addressing the methods of map generalization and simplification¡ for automatic extraction of various displays of the map¡ a new approach was used based on the dual graph. Dual graph are a modification of graph that is defined to facilitate and simplify the problems in graph. A variety of dual graphs have been used in different fields. We will show that based on the concept of one of the dual graph¡ the capabilities and efficiency of GIS in providing map with different details could be increased. Thus the topology and relationships between urban streets was involved in the extraction of various map displays.

Geographic Information Systems have many capabilities for transportation systems management. The network capabilities of GIS such as shortest path computations are very useful for transportation management. Graph theory is the base of network analysis in GIS. The current method for conversion of a transportation network to a graph is modeling the stations as nodes and the paths between stations as edges. In this paper we have proposed a new method for translation of a transportation network to a graph by dual graph concepts. Dual graphs are presented for simplifying and solving of the original graph problems. In dual aspect the transportation lines are modeled by nodes and their relations are modeled by edges. The implemented case study showed that a bus transportation network with 5 bus lines could be translated to a graph with 5 nodes and 5 edges that could be very useful in many cases، specially in evaluation of transportation system. In continuous، we have explained the wavelet transform and its applications in evaluating and planning of transportation systems. Wavelet is a mathematical transform that could extract much useful information from a signal. For instance in an innovative task، we used the wavelet transform for extracting the moment precise number of needed vehicles in every transportation lines. The implemented case study illustrates the direct relation between number of required vehicles and the rate of traffic in a bus line.

Management of transportation is one of the most important GIS applications. In this filed the network capabilities of GIS such as shortest path computation is very useful. Graph theories play an important role in GIS network analysis. Various theories such as the algorithms of computing shortest path have ever been used in different cases of graph problems. But for some important cases, there is not a good solution in primal graph. For using of dual spaces, at first the problem will be sent to a proper dual space and then after solving, the answers will come back to the primal space. In this paper, different types of dual graphs used in different sciences such as GIS, have been explained by authors. The dual graph concept for two particular problems in route specification: modeling the different costs of turns in crosses and shortest path finding between non-point origin and destination, have been used. As known, the travel time on crosses in right turning is less than left turning. In this paper it is propounded that linear dual graph can be used for modeling the left turn and right turn in a city network. A solution for finding the shortest path between non-point origin and destination was proposed. In many cases the destination or origin of the trip is not a specific point. It was shown that by changing the structure of the primal graph and its adjacent matrix, the linear or polygonal destination could be converted to a specific point. The proposed approach was implemented on the street map of a municipal district in City of Tehran. The developed application illustrated the usefulness and positive effect of discussed approach in transportation network routing.

Facilitation of transportation is one of the most important applications of Geographic Information System (GIS). In this area the network capabilities of GIS such as shortest path computation,could be very useful. Different criteria have ever considered for shortest path analysis in GIS such as: Distance, travel time, path comfort, path beauty. Travel time criterion has some random continues variations, due to its relation to traffic. Therefore, path finding based on these criterions by current algorithms such as Dijkstra is not suitable. In this field a development of algorithms that can be used on dynamic networks is necessary. In this paper we have developed an algorithm for this purpose that used statistical information of travel time in previous days for prediction of travel time in future. Also for modeling of the randomness of traffic, we have used a risk parameter for each edge in network. We have used the model of space-time partitioning for consideration of observed travel time, predicted travel time and risk parameters together. Finally for testing the developed algorithm, a case study has been explained in this paper. The implemented case study showed the usefulness of represented method in finding shortest path beside current static methods where the total travel time between two points in tested network was reduced from 35.71 minutes by static methods to 29.43 minutes. Certainly, the usefulness of our represented method could be more apparent by increased distance between origin and destination in the network.

Planning of bus transportation system is one of the most important phases in planning of public transportation systems. Such planning is quite difficult due to some inconsistent goals. For example we cannot expect paths that are planned for minimum travel time, maximum covering and access. In this connection, to obtain an optimal answer, many criteria must be considered. In this paper, a new model has been represented for planning of bus transportation systems. The recommended system takes benefit of GIS (Georaphical Information System) capabilities. This model is based on travel distribution matrix between urban blocks and have some major goals, such as the maximum number of people transferred by the system as well as the minimum travel time. The method for extraction of travel distribution matrix between urban blocks has been explained in this paper. After extraction of travel distribution matrix and its allocation to city roads we use GIS network capabilities for planning of bus lines is used. By this method one can do the planning of bus transportation paths with consideration of some major goals, simultaneously.

Management of some facilities such as transportation is one of the most important applications of geographic information systems. In this field, the network capabilities of GIS such as computation of shortest path could be very useful. There are a variety of studies and researches on developing algorithms for shortest path finding. However, less attention has been paid on modeling the uncertainty of determined optimum path. The uncertainty of a determined optimum path is relevant to the accuracy of the input data. For example, when distance is considered as a criterion for determination of optimum path, the positional accuracy of the road network affect the reliability of the determined optimum path. This paper intends to model the uncertainty of optimum paths, where the optimality is determined based on distance and travel time criteria. Error propagation rules and fuzzy set theory were used respectively to model the uncertainty for distance criteria and travel time criteria. The developed model was implemented and tested for a case study in Iran. The results showed that by including uncertainty in a path finding problem, users can determine optimum paths, which may be a little bit longer (from length or travel time perspectives), but more reliable than the shortest or the fastest path. Using a reliable optimum path is preferred by many citizens (and especially emergency services) in comparison with uncertain shortest/fastest path.

Interpolated data are usually used in many engineering and planning activities such as geology, climatology, natural resources and hazard management. Root Mean Squared Errors (RMSE) is the most frequently used indicator for error assessment and statement. Unfortunately, this indicator is mainly non-spatial and it does not provide the required spatial details about the local reliability of the interpolated layers. Therefore, development of more efficient and practically useful methods for spatial evaluation and visualization of interpolation errors are of prime importance.In this research, after reviewing some of the important limitations of RMSE and interpolation methods, a practical approach based upon the triangulation, for modeling and mapping of the reliability of interpolation has been proposed. Triangles formed by application of the delauney triangulation to sample points have been used as the main spatial entities. Three characteristics of triangles including the area, shape (modeled by the ratio of perimeter to area), and variance of the values of their 3 corners have been used to model the interpolation errors in triangle levels. The reason for choosing theseparameters is their important role in creation of errors, as well as simplicity of their calculation in GIS environment.Point data of elevation from part of Tehran metropolis has been used as the case study for examination and demonstration the usefulness of the proposed approach. Modeling has been based on the least squares fitting in a multiple regression framework. The fitted model has been used for prediction of interpolation errors. Where its validity has been evaluated by the independent, well distributed test sample points with a known elevation.Results of the proposed approach have been encouraging, and close relationship between the actual and predicted (bymodel) errors have been observed. Production of the map of interpolation errors, as in the proposed approach, can be useful for efficient use of the interpolated data. Also, these maps can be used as useful guides for collection of additional samples where the improvement of the interpolated data quality is required. More close examination of the proposed approach in a wider and diverse environmental condition has been recommended.

In order to solve some problems, as well as to simplify or facilitate some analyses in graphs, some changes can be made in the graphs. Dual graph is one of these changes. Linear dual graph is a type of dual graph that is proposed for presenting graphswith weighted nodes. In this paper, linear dual graph calculus that is based on the linear dual graph is introduced. For this purpose, at first, Linear Dual (LD1) and inverse Linear Dual (LD-1) is introduced, and then, the way of their extraction is explained. After that some applications of this calculus is explained. One of its most important applications is in specification the Hamiltonian cycle in graphs. In other words, by transportation between linear dual graph and the primal graph,we can convert the Hamiltonian cycles whose specification has always been so difficult, to Eulerian ones which can be easily recognized.