shortest path

Today, routing in urban transportation networks is considered essential with the increase in the volume of cars and traffic restrictions in metropolitan areas. Urban development, the use of personal cars has affected the external development of metropolises and has caused the pattern of suburban settlement, which new cities are concrete examples of this problem within the boundaries of metropolises.

This research is applied in terms of purpose and descriptive-analytical in terms of cognitive methodology. Considering the nature of the data and the impossibility of controlling the behavior of the effective variables in the problem, it is also non-empirical. In order to review the sources of the research, a systematic review of related sources has been used using the documentary method. In this research, in order to analyze the data, the state of dispersion of access indicators was analyzed using the GWR method, crowding optimization and fuzzy mean clustering.

Multivariate regression analysis indicates that there is a linear and direct and high correlation between the independent index and the dependent index (final access) and the identified independent indicators are able to explain 95% of the changes in access and the remaining small variances by Unknown factors are explained and predicted. By looking at the beta β values, it can be seen that the network position index has access changes compared to other indicators, and according to the access indicators, network characteristics are ranked second to fourth.

The development of a variety of public transportation systems that cover different areas, has made it difficult for passengers and users to choose the type of transportation system and appropriate route between two specified departures. In large cities such as Tehran, a network of public transportation systems, called multi-modal systems, consist of stations as nodes and public transport vehicles intermediate between the two consecutive stations as arcs, is formed. Travelers are looking continuously for a way to find the optimal route in complex multi-modal transportation networks to reach their desired destination with minimal cost and confusion. In this paper, two linear and nonlinear multi-objective programming models with three objective functions have been developed for routing in multi-modal transport systems. The objectives of the proposed model are to minimize the cost, travel time and the number of vehicle types. By examining the validation of models by test issues, two exact and meta-heuristic algorithms (ant colony algorithm) have been developed to solve the proposed model. The results of the evaluation of the performance of the solving methods indicate that problem solving by exact method for networks with more than 15 nodes are non-operating, while the meta-heuristic algorithm provides the same problems with same precision in the exact method but with logical time.

The aim of this research is to find an optimum way for the movement of manpower and military equipment in times of crisis by spending the possible least time. To this end, beginning with a review of existing studies in the field of moving troops which were effective factors in the modeling were extracted. Prioritization and selection of units deployable to crisis point, with the design of a fuzzy multi-criteria decision-making models is done according to metrics such as customer orientation, fast response, records of performance, flexibility, and distance technology to improve the ranking and fuzzy weights of the units. Considering opinions of military experts, to determine the nearest route ground transport logistics in military operations using geographic information system was implemented. By designing a linear allocation programming model, every unit of available transport facilities allocated in such a way that opportunity - cost become minimal. Finally, network of deployment projects and people and equipment unit or units selected by the related time of transportation facilities allocated was designed that enables the total deployable forces and equipment of the unit or units and calculation of the critical path of the project identifyable, control and management. The results showed that for selected units to move and logistics units to the hypothetical assumption of the origin of the crisis, regarding to taking time out of vehicle trips on the shortest route and times, 60 hours will take from the moment of notification of the order for handling and logistics of the entire selected units.