Nariman Nikoo

Bio: Nariman Nikoo is an academic researcher from Iran University of Science and Technology. The author has contributed to research in topics: Flow network & Emergency management. The author has an hindex of 4, co-authored 7 publications receiving 70 citations.

Emergency transportation network design problem: Identification and evaluation of disaster response routes

Abstract: Since disasters have considerable effects on transportation networks, the functionality of an emergency transportation network can play an important role in mitigation phase, especially in developing countries that sometimes suffer the sad experience of almost complete destruction of several cities. Transportation related disaster response activities typically include search and rescue, emergency medical care and fire-fighting trips. In this paper, the emergency transportation network design problem is proposed to determine the optimal network to perform emergency response trips with high priority in the aftermath of earthquakes. The problem has three objective functions designated to identify the optimal routes for emergency vehicles considering the length, the travel time and the number of paths as performance metrics of network vulnerability. A combined approach for considering the three objectives including weighted sum and lexicographic methods is used. The proposed model is solved using a branch-and-cut solution method. The suggested method is tested on the well-known Sioux-Falls network as well as on the real-world network of Tehran metropolis, Iran. Computational experiments are conducted to examine the effects of varying the maximum network length, and the relative weights of other objectives.

An integer programming model for analysing impacts of different train types on railway line capacity

Abstract: The evaluation of railway line capacity is an important problem, which effects majority of problems in rail transportation planning. The railway capacity is dependent on infrastructure, traffic, and operating parameters. A key factor affecting railway line capacity is the impact of different train types. As the combination of different train types increases, more interference is generated. In this paper, for evaluation of train type interactions on railway line capacity, an integer-programming model for both line and line section is presented. The problem is formulated as a multicommodity network design model on a space-discrete time network. The railway capacity is calculated using data typically available to planners. The inputs of the model are the characteristic of each train type and railway line attributes. The model determines railway capacity based on train type mixes. In addition, this model considers impact of train types on capacity and waiting time. In order to show the features of the model, a case study is implemented in Iran Railways. The capacity tends to increase non-linearly with small incremental changes in parameters. The mixture of train types reduces the railway line capacity. The proposed model can help railway managers for long-term planning. Language: en

Capacity Consumption Analysis Using Heuristic Solution Method for Under Construction Railway Routes

Abstract: In this paper, a compressed timetable is generated to calculate capacity consumption for under construction railway routes using an optimization approach. Since the detailed timetable for under construction routes does not exist, the timetable is not required in the applied model. The model generates a compressed timetable based on UIC 406 method. The capacity consumption problem is formulated as a multicommodity network design model on a space-discrete time network. A local branching heuristic algorithm is proposed to solve the model. The main idea underlining the local branching algorithm is the utilization of a general mixed integer programming solver to explore neighborhoods and locally search around the best-known solution by employing tree search. The parameters of the algorithm are tuned by using design of experiments. The proposed method is implemented in Iran Railways and the results are reported.

A subway planning bi-objective multi-period optimization model integrating timetabling and vehicle scheduling: a case study of Tehran

Abstract: Due to the interaction among different planning levels and various travel demands during a day, the transit network planning is of great importance. In this paper, a bi-objective multi-period planning model is proposed for the synchronization of timetabling and vehicle scheduling. The main aim of the problem is to minimize the weighted transfer waiting time in the interchange stations along with the operational costs of vehicles. In order to demonstrate the effectiveness of the proposed integrated model, a real case study of Tehran subway is considered. The proposed model is solved by the e-constraint method and some outstanding results are achieved.

A multi-objective emergency network design problem to carry out disaster relief operations in developing countries: A case study of Tehran, Iran

Abstract: One of the problems in post-earthquake disaster management in developing countries, such as Iran, is the prediction of the residual network available for disaster relief operations. Therefore, it is important to use methods that are executable in such countries given the limited amount of accurate data. The purpose of this paper is to present a multi-objective model that seeks to determine the set of roads of a transportation network that should preserve its role in carrying out disaster relief operations (i.e. known as “emergency road network” (ERN)) in the aftermath of earthquakes.,In this paper, the total travel time of emergency trips, the total length of network and the provision of coverage to the emergency demand/supply points have been incorporated as three important metrics of ERN into a multi-objective mixed integer linear programming model. The proposed model has been solved by adopting the e-constraint method.,The results of applying the model to Tehran’s highway network indicated that the least possible length for the emergency transportation network is about half the total length of its major roads (freeways and major arterials).,Gathering detailed data about origin-destination pair of emergency trips and network characteristics have a direct effect on designing a suitable emergency network in pre-disaster phase.,To become solvable in a reasonable time, especially in large-scale cases, the problem has been modeled based on a decomposing technique. The model has been solved successfully for the emergency roads of Tehran within about 10 min of CPU time.

A probabilistic (max,+) approach for determining railway infrastructure capacity

Abstract: We consider the problem of determining the capacity of a planned railway infrastructure layout under uncertainties. In order to address the long-term nature of the problem, in which the exact (future) demand of service is unknown, we develop a “timetable”-free approach to avoid the specification of a particular timetable. We consider a generic infra-element that allows a concise representation of many different combinations of infrastructure, safety systems and traffic regimes, such as mixed double and single track lines (e.g., a double track line including a single tunnel tube), and train operations on partly overlapping routes at station yards. We translate the capacity assessment problem for such a generic infra-element into an optimization problem and provide a solution procedure. We illustrate our approach with a capacity assessment for the newly built high-speed railway line in The Netherlands.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Abstract: Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.