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.

A spatial multi-objective optimization model for sustainable urban wastewater system layout planning

2012 ◽  
Vol 66 (2) ◽  
pp. 267-274 ◽  
Author(s):  
X. Dong ◽  
S. Zeng ◽  
J. Chen
Keyword(s):  
Optimization Model ◽  
Municipal Wastewater ◽  
Monte Carlo Sampling ◽  
Multi Objective Optimization ◽  
Urban Wastewater ◽  
Multi Objective ◽  
Local Municipality ◽  
Beijing China ◽  
System Layout

Design of a sustainable city has changed the traditional centralized urban wastewater system towards a decentralized or clustering one. Note that there is considerable spatial variability of the factors that affect urban drainage performance including urban catchment characteristics. The potential options are numerous for planning the layout of an urban wastewater system, which are associated with different costs and local environmental impacts. There is thus a need to develop an approach to find the optimal spatial layout for collecting, treating, reusing and discharging the municipal wastewater of a city. In this study, a spatial multi-objective optimization model, called Urban wastewateR system Layout model (URL), was developed. It is solved by a genetic algorithm embedding Monte Carlo sampling and a series of graph algorithms. This model was illustrated by a case study in a newly developing urban area in Beijing, China. Five optimized system layouts were recommended to the local municipality for further detailed design.

scholarly journals Multi-objective optimization of traffic signal timing using non-dominated sorting artificial bee colony algorithm for unsaturated intersections

2018 ◽  
Vol 46 (2) ◽  
pp. 85-97 ◽  
Author(s):  
Hongxing Zhao ◽  
Ruichun He ◽  
Jiangsheng Su
Keyword(s):  
Optimization Model ◽  
Artificial Bee Colony ◽  
Optimization Method ◽  
Signal Timing ◽  
Multi Objective Optimization ◽  
Abc Algorithm ◽  
Multi Objective ◽  
Bee Colony ◽  
Vehicle Delay ◽  
Single Objective

Vehicle delay and stops at intersections are considered targets for optimizing signal timing for an isolated intersection to overcome the limitations of the linear combination and single objective optimization method. A multi-objective optimization model of a fixed-time signal control parameter of unsaturated intersections is proposed under the constraint of the saturation level of approach and signal time range. The signal cycle and green time length of each phase were considered decision variables, and a non-dominated sorting artificial bee colony (ABC) algorithm was used to solve the multi-objective optimization model. A typical intersection in Lanzhou City was used for the case study. Experimental results showed that a single-objective optimization method degrades other objectives when the optimized objective reaches an optimal value. Moreover, a reasonable balance of vehicle delay and stops must be achieved to flexibly adjust the signal cycle in a reasonable range. The convergence is better in the non-dominated sorting ABC algorithm than in non-dominated sorting genetic algorithm II, Webster timing, and weighted combination methods. The proposed algorithm can solve the Pareto front of a multi-objective problem, thereby improving the vehicle delay and stops simultaneously.

scholarly journals Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Farnaz Javadi Gargari ◽  
Mahjoube Sayad ◽  
Seyed Ali Posht Mashhadi ◽  
Abdolhossein Sadrnia ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Supply Chain ◽  
Optimization Model ◽  
Optimization Problem ◽  
Programming Model ◽  
Transportation Cost ◽  
Real Data ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Hub Location ◽  
Goal Programming Model

Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

Production Modes Switch Optimization of Refinery Units

2014 ◽  
Vol 962-965 ◽  
pp. 762-767
Author(s):  
Ming Li
Keyword(s):  
Optimization Problem ◽  
Transition Period ◽  
Programming Model ◽  
Transition Process ◽  
Mixed Integer ◽  
Time Representation ◽  
Unit Operations ◽  
Long Time ◽  
Energy Consuming

Refinery units have the feature of operating inertia, long time transition period exists when production modes switch, during which product quality may decline and energy cost raises. The operating inertia have received significant attentions in actual refineries, while few literatures have given enough focus on it which is usually omitted to make scheduling easy. The core of this paper is to deal with the scheduling optimization problem of production modes switch considering operating inertia. By expression of the transition process, a mixed integer linear programming model was built based on a continuous time representation. The model optimizes unit operations by minimizing energy consuming. The formulation approach was used to address the scheduling of a refinery. Case study illustrates the model’s feasibility and efficiency.

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.

Optimization Model of the Cross Intersection Signal Timing Based on the Simulation

2015 ◽  
Vol 713-715 ◽  
pp. 1244-1247
Author(s):  
Lu Wang ◽  
Li Ying Wei ◽  
Yu Zhou
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Present Situation ◽  
Simulation Software ◽  
New Method ◽  
Signal Timing ◽  
Timing Optimization ◽  
Design Capacity ◽  
Signal Timing Optimization ◽  
The Cross

In order to solve signal timing optimization problem of the cross intersection with irregular four phases, this paper presents a new method based on the calculation of lane design capacity. There are five steps of the application in this paper: the collection and simple statistics of basic data; the analysis of present situation; the formulation and solution of signal timing optimization model; the evaluation of optimization results which are based on simulation software VISSIM; an actual example was tested to verify the feasibility of the optimization model.

Evaluation of Bus Priority Signal Strategies in Ann Arbor, Michigan

1996 ◽  
Vol 1554 (1) ◽  
pp. 74-79 ◽  
Author(s):  
Khaled A. Al-Sahili ◽  
William C. Taylor
Keyword(s):  
Field Data ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Signal Timing ◽  
Original Signal ◽  
Bus Priority ◽  
Several Variables ◽  
Ann Arbor ◽  
Vehicle Delay ◽  
Bus Travel Time

With the emergence of intelligent transportation system technologies there has been a renewed interest in the bus priority signal (BPS). The effect of providing the BPS treatment on the Washtenaw Avenue Corridor in Ann Arbor, Michigan, was studied. The NETSIM graphic animation feature was used to detect the bus arrival and award preemption. The signal timing plan was then restored to the original signal setting in subsequent cycles. The model was calibrated using field data, and the sensitivity of the model to several variables was tested. The corridor's signal timing was first optimized using the TRANSYT-7F model. The green extension and red truncation with and without compensation, the skip phase with and without compensation, and the conditional preemption plans were evaluated. It was found that in all cases signal preemption disrupts traffic progression and, thus, increases overall vehicle delay. The results of preemption were analyzed at each intersection as well as over the entire simulation network. The most appropriate preemption strategy for each intersection was determined and used in the simulation. Bus travel time and delay were reduced when this optimal BPS plan was used.

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.

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