International Journal of Transportation Engineering
Volume:7 Issue: 4, Spring 2020

In this paper, a new approach to risk minimizing vehicle routing and scheduling problem is presented. Forwarding agents or companies have two main concerns for the collection of high-risk commodities like cash or valuable commodities between the central depot and the customers: one; because of the high value of the commodities transported, the risk of ambush and robbery are very high. Two; the cost of a security guard that protects the vehicle is high. Therefore, the goals of these companies are to deliver and collect commodities with maximum security and minimum risk. Hence, in this paper, a multi-objective vehicle routing problem with time windows (VRPTW) is proposed to minimize risk and transportation costs. Finally, a memetic algorithm is designed to optimize the proposed model. The proposed algorithm is evaluated and compared with the non-dominated genetic algorithm (NSGAII) using Solomon VRPTW test sets. The results demonstrate that the presented approach is effective for valuables routing problem.

Expanding public transportation is not enough to solve the urban sprawl problem resulted from an auto-orientation perspective. So urban planning experts paid attention to integrated and coordinated planning of urban development with public transportation, which reached to sustainable urban development. The purpose of this study is to review the researches in transit-oriented development (TOD) and present practical solutions to implement TOD in Iran cities. In this paper, urban sprawl has been introduced, and three significant solutions (Smart Growth, New Urbanism, and Transit-Oriented Development) have been checked to prevent it. Then the researches in TOD allocation by various methods and modifying land uses around transit stations have been investigated. Moreover, the effects of TOD on city structure and the decisions of individuals in choosing a place of residence have been examined. Also, methods for assessment of TOD impacts and the prosperous cities, which implement the TOD, have been introduced, and finally, the practical solutions for implementing TOD in Iran cities have been presented. Based on a review of the previous studies incorporated in this paper, the practice and integration of TOD through land use and transportation showed that TOD could be the alternative solution in addressing the problems of developing the urban area.

One of user's queries from navigation service is to find the nearest facility in terms of time. The facility that is being questioned by the user as a destination may have a queuing service system (e.g. bank), which means that the cost function of the shortest path includes the waiting time at the destination as well as the travel time. This research conducts in the zone 1 of Mashhad with Bank at destination. In this research, we first calibrate the volume-travel time function to predict travel time by using history volume data of SCATS. The results of the analysis show the Moving-Average model with a period of 4 weeks is more precise to predict volumes and consequently travel time. Then we use Simulation-based method to predict waiting times in Bank. A* algorithm with different scenarios is applied to solve the shortest path problem. This algorithm is compared with the Dijkstra’s algorithm in different networks. Results show by increasing the nodes of network, the required time to solve the A* algorithm is significantly lower than the Dijkstra’s algorithm. In general, this study indicates the A* algorithm and the suggested heuristic function reduce run time for solving the shortest path problems.

Highways and in particular their pavements are the fundamental components of the road network. They require continuous maintenance since they deteriorate due to changing traffic and environmental conditions. Monitoring methods and efficient pavement management systems are needed for optimizing maintenance operations. Pavement performance prediction models are useful tools for determining the optimal time for these actions. However, incorporating the model components into a pavement management system is highly important to ensure the model efficiency. This paper presents the existing pavement performance prediction models and introduces their components. A specific model is reproduced for Tehran traffic and environmental conditions adapted from the Pavement Health Track (PHT) model. This new model comprises four different sub-models including crocodile cracks, rutting, transverse cracking, and roughness prediction models. The study presents the software tool industrialized based on the model and presents the associated calibration and validation. Validation of the model for Tehran city shows that this new model has a high prediction accuracy. Also, it is a practical tool for pavement condition predictions across Tehran as it needs fewer data requirements compared with other complicated models. This study shows that using the new model may lead to an organized maintenance budgeting as well as a decrease in time and cost of operations.

A capacitated location-routing problem (CLRP) is one of the new areas of research in distribution management. It consists of two problems; locating of facilities and routing of the vehicle with a specific capacity. The purpose of the CLRP is to open a set of stores, allocate customers to established deposits, and then design vehicle tours in order to minimize the total cost. In this paper, a new mathematical programming model for multi-depot location-routing problems is considered. This model considers heterogeneous vehicles and fuzzy travel times, which are innovative and practical limitations compared to the previous studies (e.g., simultaneous pickup and delivery). This makes the model close to real-world situations. After modeling, the fuzzy model is changed to a deterministic model by credibility theory. Since this problem belongs to a class of NP-hard ones because of its computational complexity, it is impossible to find the optimal solution in reasonable time. Therefore, a particle swarm optimization algorithm is proposed and designed to solve the presented model. To show the efficiency of the proposed PSO, its results are compared with the optimal solutions obtained by an exact method embedded in the optimization software. Furthermore, the proposed PSO is able to solve medium- and large-sized problem efficiently.

Rutting is one of the major distresses in the flexible pavements, which is heavily influenced by the asphalt mixtures properties at high temperatures. There are several methods for the characterization of the rutting resistance of asphalt mixtures. Flow number is one of the most important parameters that can be used for the evaluation of rutting. The flow number is measured by the dynamic creep test, which requires advanced equipment, notable cost, and time. This paper aims to develop a mathematical model for predicting the flow number of asphalt mixtures based on the Marshall mix design parameters using the Multivariate Adaptive Regression Spline (MARS). The required parameters for developing the model are as follows: percentage of fine and coarse aggregates, bitumen content, air voids content, voids in mineral aggregates, Marshall Stability, and flow. The coefficient of determination (R2) of the model for training and testing set is 0.96 and 0.97, respectively, which confirms the high accuracy of the model.  Moreover, the comparison of the developed model with the existing models shows the superior performance of the developed model. It should be noted that the developed model is valid only in the range of dataset used for the modeling.