Bus Priority Network Design Based on Bi-Level Programming

2015 ◽  
Vol 744-746 ◽  
pp. 1782-1785 ◽  
Author(s):  
Yi Kui Mo ◽  
Kai Wang ◽  
Shen Lv
Keyword(s):  
Network Design ◽  
Solution Algorithm ◽  
Bus Priority ◽  
Level Model ◽  
Upper Level ◽  
Bus Transportation

This paper analyzes the steps and difficulties of bus priority network design, including the bi-level characteristics of problems related to bus priority network design. Based on that, a bi-level model with the maximization of the overall bus transportation efficiency as the upper level and the minimization of bus passengers’ cost as the lower level is established and the solution algorithm of the model is studied.

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.

scholarly journals Solution Algorithm for a New Bi-Level Discrete Network Design Problem

1970 ◽  
Vol 25 (6) ◽  
pp. 513-524
Author(s):  
Qun Chen ◽  
Haibo Chen
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Solution Algorithm ◽  
Network Design Problem ◽  
Level Problem ◽  
Integer Solutions ◽  
Capacity Improvement ◽  
Upper Level ◽  
Branch Cutting ◽  
Discrete Network Design Problem

A new discrete network design problem (DNDP) was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.

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.

scholarly journals Bicycle network design: model and solution algorithm

2017 ◽  
Vol 27 ◽  
pp. 969-976 ◽  
Author(s):  
Antonio Mauttone ◽  
Gonzalo Mercadante ◽  
María Rabaza ◽  
Fernanda Toledo
Keyword(s):  
Network Design ◽  
Solution Algorithm ◽  
Design Model

Path-Based Approaches to Robust Network Design Problems Considering Boundedly Rational Network Users

2019 ◽  
Vol 2673 (3) ◽  
pp. 637-645 ◽  
Author(s):  
Longsheng Sun ◽  
Mark H. Karwan ◽  
Changhyun Kwon
Keyword(s):  
Network Design ◽  
Bounded Rationality ◽  
Shortest Paths ◽  
Unified Framework ◽  
Design Problems ◽  
Hazardous Materials Transportation ◽  
Network Design Problems ◽  
Robust Network Design ◽  
Robust Network ◽  
Upper Level

Network users may choose non-shortest paths, when (1) they satisfice with sub-optimal routes, or (2) they have perception errors of the decision environment. The notion of generalized bounded rationality has been recently proposed to create a unified framework for these two sources of behavioral uncertainty in route choices. When the notion of generalized bounded rationality is used in robust network design problems, we obtain a bi-level optimization problem with the min–max objective function at the upper level, with three layers of optimization in total. In this paper, we derive equivalent single-level path-based formulations that are readily solvable by available optimization libraries. We show how to incorporate them into robust multi-commodity network design problems in hazardous materials transportation.

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.

Park-and-Ride Network Design: A Goal Programming Approach

2014 ◽  
Vol 1030-1032 ◽  
pp. 2065-2068
Author(s):  
Xin Yuan Chen ◽  
Zhi Yuan Liu ◽  
Wei Deng
Keyword(s):  
Network Design ◽  
Goal Programming ◽  
Design Problem ◽  
Programming Model ◽  
Search Algorithm ◽  
Network Design Problem ◽  
Programming Approach ◽  
Multi Objective ◽  
Park And Ride ◽  
Upper Level

The paper addresses a park and ride network design problem in a bi-model transport network in a multi-objective decision making framework. A goal programming approach is adopted to solve the multi-objective park and ride network design problem. The goal programming approach considers the user-defined goals and priority structure, which are (i) traffic-efficient goal, (ii) total transit usage goal, (iii) spatial equity goal. This problem is formulated as a bi-level programming model. The upper level programming leads to minimize the deviation from stated goals in the context of a given priority ranking. While the lower level programming model is a modal split/traffic assignment model which is used to assess any given park and ride scheme. A heuristic tabu search algorithm is then adopted to solve this model.

Research on Uncertain Network Design Problem

2014 ◽  
Vol 505-506 ◽  
pp. 613-618
Author(s):  
Yang Wang ◽  
Jin Xin Cao ◽  
Ri Dong Wang ◽  
Xia Xi Li
Keyword(s):  
Stochastic Model ◽  
Network Design ◽  
Design Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Construction Costs ◽  
Travel Costs ◽  
Uncertain Network ◽  
Level Model ◽  
Discrete Network Design Problem

In this study, a kind of uncertain network design problem, network design problem under uncertain construction cost, is researched.The discrete network design problem under uncertain construction costs deals with the selection of links to be added to the existing network, so as to minimize the total travel costs in the network. It is assumed that the value of the demand between each pair of origin and destination is a constant and the construction costs of each potential link addition follow a certain stochastic distribution. In this paper, a bi-level and stochastic programming model for the discrete network design problem is proposed. The construction costs of potential links are assumed as random variables and mutually independent with each other in this model. The upper-level model is a chance constrain model with the objective function of minimizing the total travel costs in the network, and the lower-level model is a user equilibrium model. The stochastic model is then transformed into a deterministic one. A branch-and-bound solution algorithm is designed to solve the deterministic model in an efficient way. At last, a computational experiment is conducted to illustrate the effectiveness and efficiency of the approach proposed in this paper. The results show that the stochastic model is more flexible and practical compared with the deterministic one.

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.

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