scholarly journals Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zi Sang ◽  
Bing Zhang ◽  
Yunqiang Xue ◽  
Hongzhi Guan
Keyword(s):  
Optimization Model ◽  
Uncertainty Theory ◽  
Optimization Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Improved Genetic Algorithm ◽  
Optimization Scheme ◽  
Theoretical Support ◽  
Vehicle Operation

In the optimization process of the routes of customized buses, there are numerous uncertainties in the route planning and setting. In this study, the uncertainty theory is introduced into the optimization problem of a customized bus route, and an uncertain customized bus route optimization model is established, which aims at the minimizing the total mileage of vehicle operation. An improved genetic algorithm is used to solve the model, whose feasibility is verified by a case study. The results show that the optimization model based on the uncertainty theory can yield a reasonable customized bus route optimization scheme, and the total mileage reduced from 35.6 kilometers to 32.2 kilometers. This research provides the theoretical support for the optimization of customized bus routes.

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 Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhengyu Xie ◽  
Yong Qin
Keyword(s):  
Sensor Networks ◽  
Optimization Model ◽  
High Speed ◽  
Optimization Problem ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Railway Transport ◽  
High Speed Railway ◽  
Security Monitoring

We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

Research on the Route Optimization as to Timing Uncertainty of Wartime Transportation

2014 ◽  
Vol 556-562 ◽  
pp. 5328-5332
Author(s):  
Lin Zhu ◽  
Xiao Dun ◽  
Can Shi Zhu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Traditional Method ◽  
Uncertain Parameter ◽  
Route Optimization ◽  
Objective Functions ◽  
Improved Genetic Algorithm ◽  
Routing Optimization ◽  
Timing Uncertainty ◽  
Pass Through

Affected with various factors in wartime, the time during which the transport vehicles of military supplies pass through a certain section of a route is an uncertain parameter, whose optimization objective functions and constraints cannot be defined and solved through the traditional method of deterministic planning. In response to the problem, a routing optimization model is put forward herein for the timing uncertainty of wartime transportation and a method is devised for the Improved Genetic Algorithm to solve the routing optimization model with respect to timing uncertainty. Examples are also cited to verify the rationality of the algorithm as well as the correctness of the model.

scholarly journals Research on Coordination and Optimization of Order Allocation and Delivery Route Planning in Take-Out System

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Guofeng Sun ◽  
Zhiqiang Tian ◽  
Renhua Liu ◽  
Yun Jing ◽  
Yawen Ma
Keyword(s):  
Time Window ◽  
Route Planning ◽  
Route Optimization ◽  
Dynamic Allocation ◽  
Improved Genetic Algorithm ◽  
Time Dimension ◽  
Order Allocation ◽  
Routing Problem ◽  
Delivery Problem ◽  
Delivery Route

This paper studies the take-out route delivery problem (TRDP) with order allocation and unilateral soft time window constraints. The TRDP considers the order allocation and delivery route optimization in the delivery service process. The TRDP is a challenging version of vehicle routing problem. In order to solve this problem, this paper aims to minimize the total cost of delivery, builds an optimization model of this problem by using cumulative time, and adds time dimension in order allocation and path optimization dimensions. It can not only track the real-time location of delivery personnel but also record the delivery personnel to perform a certain task. The main algorithm is the dynamic allocation algorithm designed from the perspective of dispatch efficiency, and the subalgorithm is the improved genetic algorithm. Finally, some experiments are designed to verify the effectiveness of the established model and the designed algorithm, the order allocation and route optimization are calculated with/without the consideration of traffic jam, and the results show that the algorithm can generate better solution in each scene.

scholarly journals Multiobjective Optimization Model for Profile Design of Hump Distributing Zone

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Hongliang Zhang ◽  
Jing Yang ◽  
Taoyuan Yang
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model ◽  
Improved Genetic Algorithm ◽  
Special Equipment ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Railway Freight ◽  
Contrast Analysis ◽  
Profile Design

Railway freight trains consist of many cars heading to different destinations. Hump is the special equipment that distributes cars with different destinations to different tracks in a marshalling station. In recent years, with the development of Chinese freight car technology, the axle load has risen from 21 ton to 23 ton and will rise to 27 ton in the future. Many rolling problems appear in the hump distributing zone with the application of 23-ton axle load cars, which will be exacerbated by 27-ton axle load cars. This paper proposes a multiobjective optimization model based on the angle of the hump profile design with minimizing weighted accumulating rolling time (WART) and hump height as optimization goals and uses the improved genetic algorithm NSGA-II to determine a solution. In case study, Pareto solution set is obtained, and the contrast analysis with traditional method is made.

scholarly journals Spatial Multi-Objective Land Use Optimization toward Livability Based on Boundary-Based Genetic Algorithm: A Case Study in Singapore

2020 ◽  
Vol 9 (1) ◽  
pp. 40 ◽  
Author(s):  
Kai Cao ◽  
Muyang Liu ◽  
Shu Wang ◽  
Mengqi Liu ◽  
Wenting Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Land Use ◽  
Central Region ◽  
Optimization Model ◽  
Optimization Problem ◽  
Weighted Sum ◽  
Multi Objective ◽  
Land Use Optimization ◽  
Future Direction

In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-sum approach, followed by a boundary-based genetic algorithm adapted to help address the spatial multi-objective land use optimization problem. Furthermore, the model is successfully and effectively applied to the case study in the Central Region of Queenstown Planning Area of Singapore towards livability. In the case study, the experiments based on equal weights and experiments based on different weights combination have been successfully conducted, which can demonstrate the effectiveness of the spatial multi-objective land use optimization model developed in this research as well as the robustness and reliability of computer-generated solutions. In addition, the comparison between the computer-generated solutions and the two real planned scenarios has also clearly demonstrated that our generated solutions are much better in terms of fitness values. Lastly, the limitation and future direction of this research have been discussed.

scholarly journals Signal Timing Optimization Model Based on Bus Priority

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 325 ◽  
Author(s):  
Xu Sun ◽  
Kun Lin ◽  
Pengpeng Jiao ◽  
Huapu Lu
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Programming Model ◽  
Computing Methods ◽  
Signal Timing ◽  
Bus Priority ◽  
De Algorithm ◽  
Vehicle Delay ◽  
Beijing China

This paper focuses on the optimization problem of a signal timing design based on the concept of bus priority. This optimization problem is formulated in the form of a bi-level programming model that minimizes average passenger delay at intersections and vehicle delay in lanes simultaneously. A solution framework that implements the differential evolution (DE) algorithm is developed to efficiently solve the model. A case study based on a real-world intersection in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods. The experiment’s result shows that the optimization model can not only significantly improve the priority capacity of the buses at the intersection but also reduce the adverse impact of bus-priority approaches on the private vehicles for the intersections.

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