scholarly journals Bi-Level Model for Public Rail Transportation under Incomplete Data

2017 ◽  
Vol 17 (3) ◽  
pp. 75-91 ◽  
Author(s):  
Kristina Pavlova ◽  
Todor Stoilov ◽  
Krasimira Stoilova
Keyword(s):  
Incomplete Data ◽  
Optimization Problem ◽  
Transportation Network ◽  
Flow Distribution ◽  
Rail Transport ◽  
Rail Transportation ◽  
Maximal Flow ◽  
Level Model ◽  
Upper Level ◽  
Transportation Flows

Abstract The increase of the utilization of public rail transportations is searched in directions for redistribution of the passenger travels between rail and bus transportation. The rail transport benefits by redistribution of the transportation flows on paths, predominantly supported by rails. The redistribution of the transportation is formalized by bi-level optimization problem. The upper level optimization estimates the maximal flow, which can be transported through a transportation network, supported both by bus and rail transports. The lower level optimization gives priority to the rail transport by decreasing the costs of flow distribution, using rail transport. This bi-level optimization problem was applied for the case of optimization of the rail exploitation in Bulgaria, defining priorities in transportation of the National transport scheme.

scholarly journals Design of State Rail and Bus Transportation Scheme with Bi-Level Optimization Model

2017 ◽  
Vol 15 (4) ◽  
pp. 2-9 ◽  
Author(s):  
K. Pavlova ◽  
T. Stoilov
Keyword(s):  
Mathematical Model ◽  
Optimization Model ◽  
Optimization Problem ◽  
Transportation Network ◽  
Rail Transport ◽  
Maximal Flow ◽  
Passenger Transport ◽  
The Mathematical Model ◽  
Transportation Route ◽  
Bus Transportation

Abstract The increase of the rail public transportations is searched in directions for redistribution of the passenger travels between rail and bus transportation. The rail transport benefits by increasing it schedule for places where the transportation capacities on appropriate directions is not achieved. A mathematical model has been derived to assess the potential of the rail passenger transport to increase his capacity and efficiency. This potential has been evaluate in comparison with the competition of the bus transportation. A specific transportation route has been chosen from Sofia to Varna and the potential for increase of the rail transport has been evaluated. The mathematical model uses bi-level optimization problem, related to the evaluation of a maximal flow in a transportation network.

scholarly journals Bi-Level Operation Scheduling of Distribution Systems with Multi-Microgrids Considering Uncertainties

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1441
Author(s):  
Saeid Esmaeili ◽  
Amjad Anvari-Moghaddam ◽  
Erfan Azimi ◽  
Alireza Nateghi ◽  
João P. S. Catalão
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Optimization Problem ◽  
Point Of View ◽  
Mixed Integer ◽  
Wholesale Market ◽  
System Operator ◽  
Level Model ◽  
Upper Level ◽  
Operation Scheduling

A bi-level operation scheduling of distribution system operator (DSO) and multi-microgrids (MMGs) considering both the wholesale market and retail market is presented in this paper. To this end, the upper-level optimization problem minimizes the total costs from DSO’s point of view, while the profits of microgrids (MGs) are maximized in the lower-level optimization problem. Besides, a scenario-based stochastic programming framework using the heuristic moment matching (HMM) method is developed to tackle the uncertain nature of the problem. In this regard, the HMM technique is employed to model the scenario matrix with a reduced number of scenarios, which is effectively suitable to achieve the correlations among uncertainties. In order to solve the proposed non-linear bi-level model, Karush–Kuhn–Tucker (KKT) optimality conditions and linearization techniques are employed to transform the bi-level problem into a single-level mixed-integer linear programming (MILP) optimization problem. The effectiveness of the proposed model is demonstrated on a real-test MMG system.

scholarly journals Flexible Emergency Vehicle Network Design considering Stochastic Demands and Inverse-Direction Lanes

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Hua Wang ◽  
Ling Xiao ◽  
Zhang Chen
Keyword(s):  
Network Design ◽  
Transportation Network ◽  
Bilevel Optimization ◽  
User Equilibrium ◽  
Emergency Vehicle ◽  
Stochastic Demands ◽  
Road Users ◽  
Level Model ◽  
Access Rights ◽  
Upper Level

We study transportation network design with stochastic demands and emergency vehicle (EV) lanes. Different from previous studies, this paper considers two groups of users, auto and EV travelers, whose road access rights are differentiated in the network, and addresses the value of incorporating inverse-direction lanes in network design. We formulate the problem as a bilevel optimization model, where the upper-level model aims to determine the optimal design of EV lanes and the lower-level model uses the user equilibrium principle to forecast the route choice of road users. A simulation-based genetic algorithm is proposed to solve the model. With numerical experiments, we demonstrate the value of deploying inverse-direction EV lanes and the computational efficiency of the proposed algorithm. We reach an intriguing finding that both regular and EV lane users can benefit from building EV lanes.

Research on Charging and Discharging Dispatching Strategy for Electric Vehicles

2015 ◽  
Vol 8 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Wang Yong ◽  
Bian Haihong ◽  
Wang Chunning
Keyword(s):  
Decision Maker ◽  
Electric Vehicles ◽  
Optimization Model ◽  
Optimization Problem ◽  
Peak Load ◽  
Optimal Schedule ◽  
Negative Effects ◽  
Load Shifting ◽  
Level Model ◽  
Upper Level

The popularity of electric vehicles may lead to negative effects on the power system if the charging procedures of plug-in electric vehicles (PEVs) are uncoordinated. In order to solve the problem, the hierarchical and zonal dispatching architecture and a new bi-level optimization model are respectively presented for the charging/discharging schedules of the PEVs. The upper level model is devoted to minimizing the system load variance so as to implement peak load shifting by optimizing the dispatching plan of all periods for each electric vehicle aggregator (EVA), and the lower one is aimed at tracing the dispatching scheme determined by the upper decision-maker through presenting an optimal schedule of charging and discharging for electric vehicles in the charging areas. Two highly efficient commercial solvers, AMPL/IPOPT and AMPL/CPLEX respectively, are employed to solve the developed optimization problem. Finally, the testing IEEE system consisting of 5 agents and 30 nodes is adopted to illustrate the characteristics of the model and solving method presented in this paper.

scholarly journals Two-Level Planning of Customized Bus Routes Based on Uncertainty Theory

2021 ◽  
Vol 13 (20) ◽  
pp. 11418
Author(s):  
Bing Zhang ◽  
Zhishan Zhong ◽  
Zi Sang ◽  
Mingyang Zhang ◽  
Yunqiang Xue
Keyword(s):  
Uncertainty Theory ◽  
Optimization Problem ◽  
Operating Time ◽  
Route Planning ◽  
Theoretical Support ◽  
Level Model ◽  
Upper Level ◽  
Bus Route Planning ◽  
Two Level Model

The optimization problem of customized bus routes is affected by uncertain factors in reality; therefore, this paper introduces uncertainty theory to study the above problem. A two-level planning model that takes the maximum total revenue of the bus company as the upper-level goal and the minimum total travel cost of passengers as the lower-level goal is established, using uncertainty theory to study and solve practical problems with uncertain factors. The genetic algorithm is used to solve the model, and the feasibility of the model is verified through a case study. The research results show that the application of the two-level model of customized bus route planning based on uncertain vehicle operating time established in this paper to customize bus route planning can take into account the travel needs of passengers and high-quality experiences while also bringing benefits to enterprises and achieving a win–win situation. The research in this article provides theoretical support for the optimization of customized bus routes.

scholarly journals Evaluation of Transportation Network Reliability under Emergency Based on Reserve Capacity

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Xiongfei Zhang ◽  
Qi Zhong ◽  
Qin Luo
Keyword(s):  
Evaluation Method ◽  
Programming Model ◽  
Transportation Network ◽  
Emergency Evacuation ◽  
Reserve Capacity ◽  
Capacity Limits ◽  
Traffic Demand ◽  
Solution Algorithms ◽  
Level Model ◽  
Upper Level

There are differences between the requirements for traffic network for traffic demand in daily and emergency situations. In order to evaluate how the network designed for daily needs can meet the surging demand for emergency evacuation, the concept of emergency reliability and corresponding evaluation method is proposed. This paper constructs a bilevel programming model to describe the proposed problem. The upper level problem takes the maximum reserve capacity multiplier as the optimization objective and considers the influence of reversible lane measures taken under emergency conditions. The lower level model adopts the combined traffic distribution/assignment model with capacity limits, to describe evacuees’ path and shelter choice behavior under emergency conditions and take into account the traits of crowded traffic. An iterative optimization method is proposed to solve the upper level model, and the lower level model is transformed into a UE assignment problem with capacity limits over a network of multiple origins and single destination, by adding a dummy node and several dummy links in the network. Then a dynamic penalty function algorithm is used to solve the problem. In the end, numerical studies and results are provided to demonstrate the rationality of the proposed model and feasibility of the proposed solution algorithms.

Iterative Parametric Approach for Quadratically Constrained Bi-Level Multiobjective Quadratic Fractional Programming

2020 ◽  
Vol 17 (11) ◽  
pp. 5046-5051
Author(s):  
Vandana Goyal ◽  
Namrata Rani ◽  
Deepak Gupta
Keyword(s):  
Fractional Programming ◽  
Optimization Problem ◽  
Programming Model ◽  
Pareto Optimal Solutions ◽  
Parametric Approach ◽  
Second Stage ◽  
Quadratic Fractional Programming ◽  
Upper Level ◽  
Quadratically Constrained ◽  
Constraint Method

The paper proposed an iterative parametric approach procedure for solving Bi-level Multiobjective Quadratic Fractional Programming model. The Model is divided into two levels-upper and lower. In the first stage of the approach, a set of pareto optimal solutions of upper Level is obtained by converting the problem into equivalent single non-fractional parametric objective optimization problem by using parametric vector and ε-constraint method. Then for the second stage, the solution of upper level is followed by the lower level decision maker while finding solution with the proposed algorithm to obtain the best preferred solution. A numerical example is solved in the last to validate the feasibility of the approach.

Environmental Vibration Analysis Induced by Subway Trains Running in Overlapping Shield Tunnels

2013 ◽  
Vol 671-674 ◽  
pp. 214-217
Author(s):  
Yuan Wen Liu ◽  
Xiao Feng Ren
Keyword(s):  
Rail Transport ◽  
Vibration Source ◽  
Rail Transportation ◽  
Empirical Formulas ◽  
Linear Superposition ◽  
Vibration Attenuation ◽  
Environmental Vibration ◽  
Rail Line ◽  
Subway Train ◽  
Further Development

Environmental vibration problem caused by rail transport is always a crucial problem for the development of rail transport harmoniously and favorably. Lots of legislations have formulated to constrain this problem in many countries, however, most of them are worked out based on the analysis results and measured data from only single rail line. With the further development of rail transportation in China, more and more engineering will cross the others inevitably, which will cause a more complicated problem with multi-vibration source. And obviously, the multi-vibration source problem is not the linear superposition of several single vibration source problems. Focusing on two being planned overlapping shield tunnels, the computation model is established and the environmental vibration is calculated and analyzed by considering the running mode and running number of subway train. Fitting analysis is conducted and empirical formulas for vibration attenuation and then, the vibration range is determined accordingly. The research results in the paper can provide guide for the pre-design of overlapping engineering and also can offer references for the completion of relative legislations.

scholarly journals Hierarchical Scheduling Scheme for AC/DC Hybrid Active Distribution Network Based on Multi-Stakeholders

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2830 ◽  
Author(s):  
Chang Ye ◽  
Shihong Miao ◽  
Yaowang Li ◽  
Chao Li ◽  
Lixing Li
Keyword(s):  
Optimization Model ◽  
Distribution Network ◽  
Hierarchical Optimization ◽  
Active Distribution Network ◽  
Scheduling Scheme ◽  
Multi Stage ◽  
Flexible Loads ◽  
Level Model ◽  
Load Regulation ◽  
Upper Level

This paper presents a hierarchical multi-stage scheduling scheme for the AC/DC hybrid active distribution network (ADN). The load regulation center (LRC) is considered in the developed scheduling strategy, as well as the AC and DC sub-network operators. They are taken to be different stakeholders. To coordinate the interests of all stakeholders, a two-level optimization model is established. The flexible loads are dispatched by LRC in the upper-level optimization model, the objective of which is minimizing the loss of the entire distribution network. The lower-level optimization is divided into two sub-optimal models, and they are carried out to minimize the operating costs of the AC/DC sub-network operators respectively. This two-level model avoids the difficulty of solving multi-objective optimization and can clarify the role of various stakeholders in the system scheduling. To solve the model effectively, a discrete wind-driven optimization (DWDO) algorithm is proposed. Then, considering the combination of the proposed DWDO algorithm and the YALMIP toolbox, a hierarchical optimization algorithm (HOA) is developed. The HOA can obtain the overall optimization result of the system through the iterative optimization of the upper and lower levels. Finally, the simulation results verify the effectiveness of the proposed scheduling scheme.

scholarly journals Bi-Level Optimization for Electricity Transaction in Smart Community With Modular Pump Hydro Storage

2020 ◽  
Author(s):  
Yang Chen ◽  
Xiao Kou ◽  
Mohammed Olama ◽  
Helia Zandi ◽  
Chenang Liu ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Cost Minimization ◽  
Necessary Optimality Conditions ◽  
Local Energy ◽  
Energy Prices ◽  
Profit Distribution ◽  
Level Model ◽  
Upper Level ◽  
Smart Community ◽  
Best Responses

Abstract Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

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