scholarly journals Electric Vehicle Tour Planning Considering Range Anxiety

2020 ◽  
Vol 12 (9) ◽  
pp. 3685 ◽  
Author(s):  
Rui Chen ◽  
Xinglu Liu ◽  
Lixin Miao ◽  
Peng Yang
Keyword(s):  
Electric Vehicles ◽  
Numerical Experiments ◽  
Time Horizon ◽  
High Reliability ◽  
Route Planning ◽  
Mixed Integer ◽  
Planning Problem ◽  
Mixed Integer Linear Program ◽  
Tour Planning ◽  
Range Anxiety

In this study, the tour planning problem for electric vehicles is investigated. We aim to derive the optimal route and thus, to maximize profitability and minimize range anxiety within the time horizon. To solve this problem, a bi-objective mixed integer model is proposed. Specifically, we first introduced the reliability of route planning and quantified it as a cost with specific functions. The nonlinear model was then converted into a bi-objective mixed integer linear program, and an interactive branch and bound algorithm was adopted. Numerical experiments conducted on different networks have shown that the model that considers range anxiety offers more effective solutions. This means that our model is able to plan the routes with high reliability and low risk of profit loss and accidents.

A New Formulation for the Dial-a-Ride Problem

2021 ◽  
Author(s):  
Yannik Rist ◽  
Michael A. Forbes
Keyword(s):  
Time Window ◽  
Valid Inequalities ◽  
Route Planning ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Planning Problem ◽  
Current State ◽  
New Formulation ◽  
First Time ◽  
Delivery Location

This paper proposes a new mixed integer programming formulation and branch and cut (BC) algorithm to solve the dial-a-ride problem (DARP). The DARP is a route-planning problem where several vehicles must serve a set of customers, each of which has a pickup and delivery location, and includes time window and ride time constraints. We develop “restricted fragments,” which are select segments of routes that can represent any DARP route. We show how to enumerate these restricted fragments and prove results on domination between them. The formulation we propose is solved with a BC algorithm, which includes new valid inequalities specific to our restricted fragment formulation. The algorithm is benchmarked on existing and new instances, solving nine existing instances to optimality for the first time. In comparison with current state-of-the-art methods, run times are reduced between one and two orders of magnitude on large instances.

scholarly journals Locating Multiple Size and Multiple Type of Charging Station for Battery Electricity Vehicles

2018 ◽  
Vol 10 (9) ◽  
pp. 3267 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Huijie Wen ◽  
Cuiping Zhang
Keyword(s):  
Travel Time ◽  
Electric Vehicles ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Range Limit ◽  
Mixed Integer Linear Program ◽  
Charging Station ◽  
Different Types ◽  
Initial Charge ◽  
Charging Stations

As environmental and energy issues have attracted more and more attention from the public, research on electric vehicles has become extensive and in-depth. As driving range limit is one of the key factors restricting the development of electric vehicles, the energy supply of electric vehicles mainly relies on the building of charging stations, battery swapping stations, and wireless charging lanes. Actually, the latter two kinds of infrastructure are seldom employed due to their immature technology, relatively large construction costs, and difficulty in standardization. Currently, charging stations are widely used since, in the real world, there are different types of charging station with various levels which could be suitable for the needs of network users. In the past, the study of the location charging stations for battery electric vehicles did not take the different sizes and different types into consideration. In fact, it is of great significance to set charging stations with multiple sizes and multiple types to meet the needs of network users. In the paper, we define the model as a location problem in a capacitated network with an agent technique using multiple sizes and multiple types and formulate the model as a 0–1 mixed integer linear program (MILP) to minimize the total trip travel time of all agents. Finally, we demonstrate the model through numerical examples on two networks and make sensitivity analyses on total budget, initial quantity, and the anxious range of agents accordingly. The results show that as the initial charge increases or the budget increases, travel time for all agents can be reduced; a reduction in range anxiety can increase travel time for all agents.

scholarly journals The Mobile Charging Vehicle Routing Problem with Time Windows and Recharging Services

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Hui Chen ◽  
Cuiping Zhang
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Routing Problem ◽  
Battery Electric Vehicles ◽  
Battery Capacity

For the environmental friendliness of the technology on battery electric vehicles, there is growing attention on it. However, the market share of battery electric vehicles remains low due to the range anxiety. As a remedy, the mobile charging services could offer charging service at any time or locations requested. For profitability of the services, the operator should route the charging vehicles in a more efficient manner. For this consideration, we formulate the mobile charging vehicle routing problem as a mixed integer linear program based on the classical vehicle routing problem with time windows. To demonstrate the model, test instances are designed and computational results are presented. In order to examine the change of the number of mobile charging vehicles and travel distance, sensitivity analyses, such as battery capacity and recharging rate, are performed. The results show that larger battery capacity, quicker charging rate, or higher service efficiency could decrease the number of mobile charging vehicles and total traveled distances, respectively.

Security Constrained Economic Dispatch

2012 ◽  
pp. 306-321
Author(s):  
Lizhi Wang ◽  
Nan Kong
Keyword(s):  
Power System ◽  
Transmission Line ◽  
Electric Power ◽  
Transmission Lines ◽  
High Reliability ◽  
Low Cost ◽  
Load Shedding ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Markov Decision

The main objective of electric power dispatch is to provide electricity to the customers at low cost and high reliability. Transmission line failures constitute a great threat to the electric power system security. We use a Markov decision process (MDP) approach to model the sequential dispatch decision making process where demand level and transmission line availability change from hour to hour. The action space is defined by the electricity network constraints. Risk of the power system is the loss of transmission lines, which could cause involuntary load shedding or cascading failures. The objective of the model is to minimize the expected long-term discounted cost (including generation, load shedding, and cascading failure costs). Policy iteration can be used to solve this model. At the policy improvement step, a stochastic mixed integer linear program is solved to obtain the optimal action. We use a PJM network example to demonstrate the effectiveness of our approach.

scholarly journals Two - Echelon Vehicle Routing Problem with Recharge Stations

2019 ◽  
Vol 20 (4) ◽  
pp. 305-317
Author(s):  
Anita Agárdi ◽  
László Kovács ◽  
Tamás Bányai
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Manufacturing Systems ◽  
Route Planning ◽  
Planning Problem ◽  
Test Results ◽  
Routing Problem ◽  
Efficient Operation ◽  
Wide Range

Abstract The efficient operation of logistic processes requires a wide range of design tasks to ensure efficient, flexible and reliable operation of connected production and service processes. Autonomous electric vehicles support the flexible in-plant supply of cyber-physical manufacturing systems. Within the frame of this article, the extension of the Two-Echelon Vehicle Routing Problem with recharge stations is analyzed. The objective function of the optimization problem is the minimization of operation costs. The extension of 2E-VRP means that the second level vehicles (electric vehicles, must be recharged) come from one recharge station, then pick up the products from the satellite, visit the customers and return to the recharge station from where it started. We solved the route planning problem with the application of construction heuristics and improvement heuristics. The test results indicate that the combination of this approach provides a superior efficiency.

scholarly journals The Energy-Efficient Dynamic Route Planning for Electric Vehicles

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Wenjuan Zhou ◽  
Li Wang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Electric Vehicles ◽  
Energy Efficient ◽  
Programming Model ◽  
Transportation Network ◽  
Route Planning ◽  
Planning Problem ◽  
Total Energy Consumption ◽  
Driving Mode

Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresses the route planning problem in dynamic transportation network where the link travel times are assumed to be random variables to minimize total energy consumption and travel time. The changeable signals are introduced to establish state-space-time network to describe the realistic dynamic traffic network and also used to adjust the travel time according to the signal information (signal cycle, green time, and red time). By adjusting the travel time, the electric vehicle can achieve a nonstop driving mode during the traveling. Further, the nonstop driving mode could avoid frequent acceleration and deceleration at the signal intersections so as to reduce the energy consumption. Therefore, the dynamically adjusted travel time can save the energy and eliminate the waiting time. A multiobjective 0-1 integer programming model is formulated to find the optimal routes. Two methods are presented to transform the multiobjective optimization problem into a single objective problem. To verify the validity of the model, a specific simulation is conducted on a test network. The results indicate that the shortest travel time and the energy consumption of the planning route can be significantly reduced, demonstrating the effectiveness of the proposed approaches.

scholarly journals Bundle Pricing Decisions for Fresh Products with Quality Deterioration

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Fang ◽  
Yiping Jiang ◽  
Xingxing Han
Keyword(s):  
Numerical Experiments ◽  
Programming Model ◽  
Mixed Integer ◽  
Quality Requirement ◽  
Mixed Integer Linear Program ◽  
Pricing Decisions ◽  
Quality Deterioration ◽  
Decision Variables ◽  
Reservation Prices ◽  
Fresh Products

How to sell fresh products quickly to decrease the storage cost and to meet customer quality requirement is of vital importance in the food supply chain. Bundling fresh products is an efficient strategy to promote sales and reduce storage pressure of retailers. In this paper, we consider the bundle pricing decisions for homogeneous fresh products with quality deterioration. The value of fresh products with quality deterioration is approximated as an exponential function based on which customer’s reservation prices are calculated. A nonlinear mixed integer programming model is used to formulate the bundle pricing problem for fresh products. By adding auxiliary decision variables, this model is converted into a mixed integer linear program. Numerical experiments and sensitive analysis are conducted to provide managerial insights for bundling fresh products with quality deterioration.

Security Constrained Economic Dispatch

2010 ◽  
Vol 1 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Lizhi Wang ◽  
Nan Kong
Keyword(s):  
Power System ◽  
Transmission Line ◽  
Electric Power ◽  
High Reliability ◽  
Low Cost ◽  
Electric Power System ◽  
Load Shedding ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Discounted Cost

The main objective of electric power dispatch is to provide electricity to the customers at low cost and high reliability. Transmission line failures constitute a great threat to the electric power system security. We use a Markov decision process (MDP) approach to model the sequential dispatch decision making process where demand level and transmission line availability change from hour to hour. The action space is defined by the electricity network constraints. Risk of the power system is the loss of transmission lines, which could cause involuntary load shedding or cascading failures. The objective of the model is to minimize the expected long-term discounted cost (including generation, load shedding, and cascading failure costs). Policy iteration can be used to solve this model. At the policy improvement step, a stochastic mixed integer linear program is solved to obtain the optimal action. We use a PJM network example to demonstrate the effectiveness of our approach.

Route planning of intelligent bridge cranes based on an improved artificial potential field method

2021 ◽  
pp. 1-8
Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li
Keyword(s):  
Potential Field ◽  
Autonomous Navigation ◽  
Route Planning ◽  
Simple Algorithm ◽  
Field Method ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Operating Characteristics ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.

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