A shortest path algorithm for the departure time and speed optimization problem

We present a shortest-path algorithm for the departure time and speed optimization problem under traffic congestion. The objective of the problem is to determine an optimal schedule for a vehicle visiting a fixed sequence of customer locations to minimize a total cost function encompassing emissions cost and labor cost.We account for the presence of traffic congestion, which limits the vehicle speed during peak hours.We show how to cast this problem as a shortest-path problem by exploiting some structural results of the optimal solution. We illustrate the solution method and discuss some properties of the problem.</p

Potential of Mobile Energy Hubs for Enhancing Resilience of Electricity Distribution Systems

In this paper, an operational framework is presented to improve electrical distribution network resilience based on the Mobile Energy Hubs (MEHs) concept. In fact, critical loads should be immediately islanded in a post-flood state and then recovered. Accordingly, this paper focuses on providing an effective management solution to enhance the functioning of electricity distribution systems with the objective of maximizing restoration of critical loads and minimizing their restoration time span based on MEH. To this end, MEHs are installed on trucks to deliver the required power for supplying the islanded critical loads in zones affected by a flood. Besides, in order to demonstrate a practical resilient structure, possible damage inflicted on other critical infrastructures is considered. Moreover, obstacles resulting from the destruction of the transportation infrastructure caused by a flood are overcome by using the shortest path algorithm (SPA). In this case, the optimization algorithm determines the shortest possible path for transporting the MEHs to supply critical loads in the least time aiming to improve the network resilience indicators. Finally, the proposed framework is studied in a standard test electricity distribution network. Simulations are carried out to evaluate the network resilience indicators of the proposed framework in obtaining a resilient distribution network during natural disasters.© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

A new approach to speed optimization of empty platform wagons in the Southeast region of Brazil / Uma nova abordagem para a otimização de velocidade de vagões de plataforma vazios na região Sudeste Do Brasil

Matching the demand for rail freight transportation depends on the railroad network structure and the availability of the rolling stock, locomotives and wagons. The distribution of wagons optimization helps reduce transportation costs, and the efficient allocation of assets is essential for rail competitiveness with other means of transportation. The present study aims to develop a mathematical model for optimizing the allocation of wagons and minimizing the distribution cost, adopted as empty transit time. The model also calculates the empty transit time of wagons according to demand distribution, and reduces the necessity for rail freight assets, because it also minimizes the wagon cycle. An algorithm was developed from the characteristics related to the distribution of freight wagons, using planned cycles adjusted by the demand distribution, and mathematical modeling was performed, applying integer linear programming to minimize the empty wagon transit time in a railway company. As a result, a weighted and optimized cycle was obtained to perform the sizing of wagons and meet the transportation plan, as well as minimizing the transit time between unloading and loading of goods. The new model presents a contribution to the operation, because, in addition to directing the optimal distribution of the assets using an integer linear programming algorithm, it also allows the planned wagon cycle adequacy, according to the demand of the respective period

A shortest path algorithm for the departure time and speed optimization problem

\u3cp\u3eWe present a shortest-path algorithm for the departure time and speed optimization problem under traffic congestion. The objective of the problem is to determine an optimal schedule for a vehicle visiting a fixed sequence of customer locations to minimize a total cost function encompassing emissions cost and labor cost.We account for the presence of traffic congestion, which limits the vehicle speed during peak hours.We show how to cast this problem as a shortest-path problem by exploiting some structural results of the optimal solution. We illustrate the solution method and discuss some properties of the problem.\u3c/p\u3

A shortest path algorithm for the departure time and speed optimization problem

We present a shortest-path algorithm for the departure time and speed optimization problem under traffic congestion. The objective of the problem is to determine an optimal schedule for a vehicle visiting a fixed sequence of customer locations to minimize a total cost function encompassing emissions cost and labor cost.We account for the presence of traffic congestion, which limits the vehicle speed during peak hours.We show how to cast this problem as a shortest-path problem by exploiting some structural results of the optimal solution. We illustrate the solution method and discuss some properties of the problem