scholarly journals Optimal Design of Cordon Sanitaire for Regular Epidemic Control

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hongzhi Lin
Keyword(s):  
Programming Model ◽  
Queueing Network ◽  
Optimal Solution ◽  
Epidemic Control ◽  
Level Model ◽  
Optimal Deployment ◽  
State And Local ◽  
Upper Level ◽  
Bilevel Programming Model ◽  
Cordon Sanitaire

The outbreak of COVID-19 has disrupted our regular life. Many state and local authorities have enforced a cordon sanitaire for the protection of sensitive areas. Travelers can only travel across the cordon after being qualified. This paper aims to propose a method to determine the optimal deployment of cordon sanitaire in terms of the number of parallel checkpoints at each entry link for regular epidemic control. A bilevel programming model is formulated where the lower-level is the transport system equilibrium with queueing to predict traffic inflow, and the upper-level is queueing network optimization, which is an integer nonlinear programming. The objective of this optimization is to minimize the total operation cost of checkpoints with a predetermined maximum waiting time. Note that stochastic queueing theory is used to represent the waiting phenomenon at each entry link. A heuristic algorithm is designed to solve the proposed bilevel model where the method of successive averages (MSA) is adopted for the lower-level model, and the genetic algorithm (GA) is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that the methods can find a good heuristic optimal solution. These methods are useful for policymakers to determine the optimal deployment of cordon sanitaire for hazard prevention and control.

scholarly journals The Shrinking of Beijing and the Rising of Xiong’an: Optimize Population Migration in terms of Transport Service

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Hongzhi Lin
Keyword(s):  
Bilevel Programming ◽  
Central Government ◽  
Programming Model ◽  
Service Level ◽  
User Equilibrium ◽  
Population Migration ◽  
Transport Service ◽  
Level Model ◽  
Upper Level ◽  
Bilevel Programming Model

The population of Beijing has already come to its loading capacity. The China central government plans to build an ideal city named Xiong’an nearby Beijing. The city is expected to work as a carrying hub for noncapital functions of Beijing. The central government does not rush to build before a deliberated urban planning is accomplished. For sustainable development, a difficulty faced by urban planners is that the maximum number of people can be migrated from Beijing to Xiong’an with constraint on level of transport service. This paper developed a specialized bilevel programming model where the upper level is to ensure a predetermined transport service level regarding to population migration, while the lower level is feedback equilibrium between trip generation and traffic assignment. To be more specific, trip is generated by the gravity model, and traffic is assigned by the user equilibrium model. It is well known that the bilevel programming problem is tough and challenging. A try-and-error algorithm is designed for the upper-level model, and a method of successive average (MSA) is developed for the lower-level model. The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. It shows that the methods can be very useful to identify the maximum population migration subject to level of transport service.

Optimal Deployment of Cordon Sanitaire with Available Testing Capacity

2021 ◽  
pp. 036119812110556
Author(s):  
Hongzhi Lin ◽  
Yongping Zhang
Keyword(s):  
Traffic Flow ◽  
Waiting Time ◽  
Road Network ◽  
Travel Demand ◽  
Nonlinear Integer Programming ◽  
Network Equilibrium ◽  
Level Model ◽  
Optimal Deployment ◽  
Upper Level ◽  
Cordon Sanitaire

During the COVID-19 pandemic, authorities in many places have implemented various countermeasures, including setting up a cordon sanitaire to restrict population movement. This paper proposes a bi-level programming model to deploy a limited number of parallel checkpoints at each entry link around the cordon sanitaire to achieve a minimum total waiting time for all travelers. At the lower level, it is a transportation network equilibrium with queuing for a fixed travel demand and given road network. The feedback process between trip distribution and trip assignment results in the predicted waiting time and traffic flow for each entry link. For the lower-level model, the method of successive averages is used to achieve a network equilibrium with queuing for any given allocation decision from the upper level, and the reduced gradient algorithm is used for traffic assignment with queuing. At the upper level, it is a queuing network optimization model. The objective is the minimization of the system’s total waiting time, which can be derived from the predicted traffic flow and queuing delay time at each entry link from the lower-level model. Since it is a nonlinear integer programming problem that is hard to solve, a genetic algorithm with elite strategy is designed. An experimental study using the Nguyen-Dupuis road network shows that the proposed methods effectively find a good heuristic optimal solution. Together with the findings from two additional sensitivity tests, the proposed methods are beneficial for policymakers to determine the optimal deployment of cordon sanitaire given limited resources.

scholarly journals Optimizing Bus Frequencies under Uncertain Demand: Case Study of the Transit Network in a Developing City

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Zhengfeng Huang ◽  
Gang Ren ◽  
Haixu Liu
Keyword(s):  
Travel Time ◽  
Programming Model ◽  
Uncertain Demand ◽  
Transit Assignment ◽  
Transit System ◽  
Transit Network ◽  
Passenger Demand ◽  
Level Model ◽  
Upper Level ◽  
Bilevel Programming Model

Various factors can make predicting bus passenger demand uncertain. In this study, a bilevel programming model for optimizing bus frequencies based on uncertain bus passenger demand is formulated. There are two terms constituting the upper-level objective. The first is transit network cost, consisting of the passengers’ expected travel time and operating costs, and the second is transit network robustness performance, indicated by the variance in passenger travel time. The second term reflects the risk aversion of decision maker, and it can make the most uncertain demand be met by the bus operation with the optimal transit frequency. With transit link’s proportional flow eigenvalues (mean and covariance) obtained from the lower-level model, the upper-level objective is formulated by the analytical method. In the lower-level model, the above two eigenvalues are calculated by analyzing the propagation of mean transit trips and their variation in the optimal strategy transit assignment process. The genetic algorithm (GA) used to solve the model is tested in an example network. Finally, the model is applied to determining optimal bus frequencies in the city of Liupanshui, China. The total cost of the transit system in Liupanshui can be reduced by about 6% via this method.

scholarly journals Parcel Locker Location Based on a Bilevel Programming Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Gege Yang ◽  
Yin Huang ◽  
Ying Fu ◽  
Biao Huang ◽  
Sishi Sheng ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Bilevel Programming ◽  
Consumer Satisfaction ◽  
Programming Model ◽  
Optimal Location ◽  
Network Efficiency ◽  
Demand Distribution ◽  
Level Model ◽  
Upper Level ◽  
Bilevel Programming Model

In order to improve delivery network efficiency and to solve consumer satisfaction problems, parcel locker location optimisation scheme is proposed based on the delivery demand under the e-commerce environment. In this paper, a bilevel programming (BLP) model is established to identify the optimal location for parcel lockers by considering benefits of consumers and logistics planning departments. The upper-level model is to determine the optimal location by minimising the planners’ cost, and the lower one gives an equilibrium demand distribution by minimising the consumers’ pick-up cost. On the special form of constraints, a bilevel genetic algorithm is proposed based on GIS data and a genetic algorithm. Finally, a numerical example is employed to demonstrate the application of the method, which indicates that the model can solve the problem of parcel locker location.

Reduction of Dimension of the Upper Level Problem in a Bilevel Programming Model Part 2

2011 ◽  
pp. 265-272 ◽  
Author(s):  
Vyacheslav V. Kalashnikov ◽  
Stephan Dempe ◽  
Gerardo A. Pérez-Valdés ◽  
Nataliya I. Kalashnykova
Keyword(s):  
Bilevel Programming ◽  
Programming Model ◽  
Level Problem ◽  
Reduction Of Dimension ◽  
Upper Level ◽  
Bilevel Programming Model

Integrated optimization of production planning and scheduling in uncertain re-entrance environment for fixed-position assembly workshops

2022 ◽  
pp. 1-18
Author(s):  
Nan-Yun Jiang ◽  
Hong-Sen Yan
Keyword(s):  
Genetic Algorithm ◽  
Production Planning ◽  
Programming Model ◽  
Expected Value ◽  
Fixed Position ◽  
Planning And Scheduling ◽  
Integrated Optimization ◽  
Production Planning And Scheduling ◽  
Level Model ◽  
Upper Level

For the fixed-position assembly workshop, the integrated optimization problem of production planning and scheduling in the uncertain re-entrance environment is studied. Based on the situation of aircraft assembly workshops, the characteristics of fixed-position assembly workshop with uncertain re-entrance are abstracted. As the re-entrance repetition obeys some type of probability distribution, the expected value is used to describe the repetition, and a bi-level stochastic expected value programming model of integrated production planning and scheduling is constructed. Recursive expressions for start time and completion time of assembly classes and teams are confirmed. And the relation between the decision variable in the lower-level model of scheduling and the overtime and earliness of assembly classes and teams in the upper-level model of production planning is identified. Addressing the characteristics of bi-level programming model, an alternate iteration method based on Improved Genetic Algorithm (AI-IGA) is proposed to solve the models. Elite Genetic Algorithm (EGA) is introduced for the upper-level model of production planning, and Genetic Simulated Annealing Algorithm based on Stochastic Simulation Technique (SS-GSAA) is developed for the lower-level model of scheduling. Results from our experiments demonstrate that the proposed method is feasible for production planning and optimization of the fixed-position assembly workshop with uncertain re-entrance. And algorithm comparison verifies the effectiveness of the proposed algorithm.

scholarly journals Bilevel programming model and algorithms for flight gate assignment problem

2020 ◽  
Vol 124 (1281) ◽  
pp. 1667-1682
Author(s):  
J. Lin ◽  
X. Ding ◽  
H. Li ◽  
J. Zhou
Keyword(s):  
Bilevel Programming ◽  
Programming Model ◽  
Eastern China ◽  
The Other ◽  
Adaptive Genetic Algorithm ◽  
Transfer Time ◽  
Objective Functions ◽  
Upper Level ◽  
Bilevel Programming Model ◽  
Bilevel Optimisation

ABSTRACTConsidering the decision-making requirements of airport, airlines and passengers, a bilevel programming model which contains two parts was proposed in this paper. One part is to improve the utilization of gates of the airport (upper level), so the objective function of the upper level to the minimum overall variance of slack time between two consecutive air crafts at the same gate. The other part looks at maximize the airline revenue and passengers more conveniently and comfortably (lower level). The lower level has two objective functions — the minimum passenger transfer failure and the minimum passenger average transfer time, respectively. According to the latest data of an airport in Eastern China, the adaptive genetic algorithm is used to solve the above-mentioned bilevel optimisation problems. The numerical experiment shows that the model not only reduces the variance of the relaxation time, but also optimises the flight gate allocation and achieves the initial goal.

Collaboration optimization model of dynamic traffic control and guidance based on Internet of Vehicles

2018 ◽  
Vol 32 (22) ◽  
pp. 1850253
Author(s):  
Zhi-Yuan Sun ◽  
Yue Li ◽  
Wen-Cong Qu ◽  
Yan-Yan Chen
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Optimization Model ◽  
Programming Model ◽  
Urban Traffic ◽  
Middle Level ◽  
Internet Of Vehicles ◽  
Model Based ◽  
Level Model ◽  
Upper Level

In order to improve the comprehensive effect of Urban Traffic Control System (UTCS) and Urban Traffic Flow Guidance System (UTFGS), this paper puts forward a collaboration optimization model of dynamic traffic control and guidance based on Internet of Vehicles (IOV). With consideration of dynamic constraints of UTCS and UTFGS, UTCS is taken as the fast variable, and UTFGS is taken as the slow variable in the collaboration optimization modeling. The conception of Variable Cycle Management (VCM) is presented to solve the mathematical modeling problem under the background of the two variables. A unified framework for VCM is proposed based on IOV. The delay and travel time are calculated based on lane-group-based cell transmission model (LGCTM). The collaboration optimization problem is abstracted into a tri-level programming model. The upper level model is a cycle length optimization model based on multi-objective programming. The middle level model is a dynamic signal control decision model based on fairness analysis. The lower level model is a user equilibrium model based on average travel time. A Heuristic Iterative Optimization Algorithm (HIOA) is set up to solve the tri-level programming model. The upper level model is solved by Non-dominated Sorting Genetic Algorithm II (NSGA II), the middle level model and the lower level model are solved by Method of Successive Averages (MSA). A case study shows the efficiency and applicability of the proposed model and algorithm.

Bi-Level Programming Model and Solution Algorithm for the Location of E-Business Logistics Distribution

2014 ◽  
Vol 1030-1032 ◽  
pp. 2532-2537
Author(s):  
Zhi Ping Du ◽  
Feng Zhi Qi
Keyword(s):  
Programming Model ◽  
Current Status ◽  
Fixed Costs ◽  
Transport Costs ◽  
Customer Demand ◽  
Customer Choice ◽  
Level Model ◽  
Upper Level ◽  
End Node ◽  
The Impact

For the current status of e-commerce logistics and distribution terminal node layout,this article considers planners and customers both benefit, while also considering the impact of the end node distribution route for cost.A bi-level programming model of end nodes location was constructed. The upper level model is the smallest in the conditions of transport costs and fixed costs as much as possible to attract customer demand, lower programming model considers the distance, the price of services and quality of service that influence customer choice behavior, and customer demand for the costs of terminal nodes distribution is studied.Finally, a numerical example verifies the feasibility of the model and algorithm.

scholarly journals Multicriteria Intermodal Freight Network Optimal Problem with Heterogeneous Preferences under Belt and Road Initiative

2020 ◽  
Vol 12 (24) ◽  
pp. 10265
Author(s):  
Zhuo Zhang ◽  
Dezhi Zhang ◽  
Lóránt A. Tavasszy ◽  
Qinglin Li
Keyword(s):  
Network Optimization ◽  
Programming Model ◽  
Preference Heterogeneity ◽  
Heterogeneous Preferences ◽  
Proposed Model ◽  
Belt And Road ◽  
China Railway ◽  
The Government ◽  
Upper Level ◽  
Bilevel Programming Model

In this study, we demonstrate the importance of incorporating shippers’ preference heterogeneity into the optimization of the China Railway express network. In particular, a bilevel programming model is established to minimize the total construction cost for the government in the upper level and maximize the shippers’ satisfaction in the lower level. The proposed model considers price, time, reliability, frequency, safety, flexibility, traceability, and emission. Two designs are obtained by applying the model to two scenarios, in which one is of the aggregate shipper group and the other is of the three distinct clusters. Results show that explicitly including heterogeneity in network optimization pays off in terms of the dramatic increase in shippers’ satisfaction and the share of the sustainable railway without generating extra cost for the system. The results of this study could lead to insightful implication for proper network planning for the China Railway express and some useful suggestions on the subsidies of the government.

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