scholarly journals Optimizing Strategies for the Urban Work Zone with Time Window Constraints

2019 ◽  
Vol 11 (15) ◽  
pp. 4218 ◽  
Author(s):  
Yao Yu ◽  
Jinxian Weng ◽  
Wanying Zhu
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Time Window ◽  
Optimal Solution ◽  
Nonlinear Program ◽  
Road Maintenance ◽  
Optimization Strategy ◽  
Variable Speed Limit ◽  
Travel Delay ◽  
Time Window Constraints

Work zones that move with road maintenance tasks are enclosing and have caused severe traffic jams and the significant decline of road capacity. This paper proposes an intelligent-based multi-objects road maintenance optimization strategy based on a practical origin–destination (OD) matrix and complicated work schedules over a real urban road network. It focuses on the optimization of multi short-term maintenance tasks and the minimization of average travel delay for vehicles passing through. By taking the driving characteristic into account, static and dynamic variable speed limit strategies provide access to ensure safety on the working road network. Through this view, the problem was formulated as a mixed multi-object nonlinear program (MNLP) model with respect to the time window of the related sub-maintenance task. By using actual OD distribution matrix data, a series of microscopic simulated cases were conducted to test the model’s validity. Moreover, sensitive analyses of types of parameters (e.g., traffic safety threshold, traffic flow and working efficiency) with an optimal solution were discussed considering five different scenarios.

scholarly journals The Optimization Model of Ride-Sharing Route for Ride Hailing Considering Both System Optimization and User Fairness

2021 ◽  
Vol 13 (2) ◽  
pp. 902
Author(s):  
Yi Cao ◽  
Shan Wang ◽  
Jinyang Li
Keyword(s):  
Optimization Model ◽  
Road Network ◽  
Time Window ◽  
Supply And Demand ◽  
Optimal Solution ◽  
System Optimization ◽  
Urban Traffic ◽  
Route Optimization ◽  
Operating Efficiency ◽  
Ride Sharing

To fully take the advantages of ride-sharing ride hailing, such as high loading rate, high operating efficiency, and less traffic resources, and to alleviate the difficulty of getting a taxi in urban hubs, the topic of ride-sharing route optimization for ride hailing is studied in this paper. For the multiple ride hailing ride-sharing demands and multiple ride hailing services in the urban road network in a specific period, the objective function is established with the shortest route of the system. The constraint conditions of the optimization model are constructed by considering factors of the rated passenger capacity, route rationality, passenger benefits, driver benefits and time window. Based on the idea of the Genetic Algorithm, the solution algorithm of the optimization model is developed. According to the supply and demand data of taxi during peak hours in the local road network in the city of Dalian, the optimization model and algorithm are used to optimize the ride-sharing route scheme. Research results indicate that the optimization model and algorithm can find the approximate optimal solution of the system in a short time. Compared with the traditional non-ride-sharing mode, the ride-sharing scheme can not only effectively reduce the taxi empty-loaded rate and the travel cost of passengers, improve the efficiency of drivers, but also save energy and reduce emissions, and promote the sustainable development of urban traffic.

A Cooperative Scheduling Model for Subway Trains

2012 ◽  
Author(s):  
Xiang Li ◽  
Xin Yang ◽  
Hongwei Wang ◽  
Shuai Su ◽  
Wenzhe Sun
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Electric Energy ◽  
Optimal Solution ◽  
Optimization Approach ◽  
Trip Time ◽  
Proposed Model ◽  
Time Window Constraints ◽  
Braking Phase ◽  
Cooperative Scheduling

For subway systems, the energy put into accelerating the trains can be reconverted into electric energy by using the motors as generators during braking phase. Generally speaking, except a small part is used for on-board purposes, most of the recovery energy is transmitted backwards along the conversion chain and fed back into the catenary. However, since the low catenary voltage DC systems, the transmission losses are very high. In order to improve the utilization of recovery energy, this paper proposes an optimization approach to cooperate the acceleration and brake times of successive trains such that the recovery energy from the braking train can be directly used by the accelerating train. First, we formulate a quadratic programming model to optimize the cooperative degree with trip time constraint and time window constraints. Furthermore, we solve the optimal solution by using the Kuhn-Tucker conditions. Finally, we present a numerical example based on the operation data from Beijing Yizhuang subway line of China, which illustrates that the proposed model can improve the cooperative degree by 9.08%.

scholarly journals Simultaneous Optimization of the Liner Shipping Route and Ship Schedule Designs with Time Windows

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xi Jiang ◽  
Haijun Mao ◽  
Hao Zhang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Time Windows ◽  
Operating Cost ◽  
Optimal Solution ◽  
Liner Shipping ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Time Window Constraints ◽  
Call Sequence

This paper proposes to address the problem of the simultaneous optimization of the liner shipping route and ship schedule designs by incorporating port time windows. A mathematical programming model was developed to minimize the carrier’s total operating cost by simultaneously optimizing the port call sequence, ship arrival time per port of call, and sailing speed per shipping leg under port time window constraints. In view of its structure, the nonlinear nonconvex optimization model is further transformed into a mixed-integer linear programming model that can be efficiently solved by extant solvers to provide a global optimal solution. The results of the numerical experiments performed using a real-world case study indicated that the proposed model performs significantly better than the models that handle the design problems separately. The results also showed that different time windows will affect the optimal port call sequence. Moreover, port time windows, bunker price, and port efficiency all affect the total operating cost of the designed shipping route.

scholarly journals Road Investment and Traffic Safety: An International Study

2020 ◽  
Vol 12 (16) ◽  
pp. 6332 ◽  
Author(s):  
Francisco Calvo-Poyo ◽  
José Navarro-Moreno ◽  
Juan de Oña
Keyword(s):  
Traffic Safety ◽  
Data Model ◽  
Road Network ◽  
International Study ◽  
Complex Problem ◽  
Economic Resources ◽  
Road Mortality ◽  
Fatality Rate ◽  
Road Maintenance ◽  
Road Fatality

The aim of this study is to analyse whether the economic resources invested in roads—both investment in construction and expenditure on maintenance and conservation—have any influence on road fatality rates. Since this is a complex problem, and because there are many factors that can influence the fatality rate, other variables related to specific transport, socioeconomic and meteorological factors are also considered. The study was carried out using a panel data model, modelling road mortality as a function of 12 variables. The scope of the study is international, focusing on the interurban road network. Data were collected from 23 European countries for the period 1998–2016. The main results obtained are that both expenditure on road maintenance and conservation and the proportion of motorways in the total road network contribute to reducing road mortality. Contrariwise, greater investment in construction leads to an increase in the fatality rate.

Simulation and Performance Analysis of Tilted Time Window and Support Vector Machine Based Learning Object Ranking Method

2020 ◽  
Vol 13 (2) ◽  
pp. 153-164
Author(s):  
Narina Thakur ◽  
Deepti Mehrotra ◽  
Abhay Bansal ◽  
Manju Bala
Keyword(s):  
Support Vector Machine ◽  
Classification Accuracy ◽  
Time Window ◽  
Optimal Solution ◽  
Similarity Score ◽  
Learning Objects ◽  
Retrieval Algorithm ◽  
Support Vector ◽  
Computationally Efficient ◽  
User Query

Objective: Since the adequacy of Learning Objects (LO) is a dynamic concept and changes in its use, needs and evolution, it is important to consider the importance of LO in terms of time to assess its relevance as the main objective of the proposed research. Another goal is to increase the classification accuracy and precision. Methods: With existing IR and ranking algorithms, MAP optimization either does not lead to a comprehensively optimal solution or is expensive and time - consuming. Nevertheless, Support Vector Machine learning competently leads to a globally optimal solution. SVM is a powerful classifier method with its high classification accuracy and the Tilted time window based model is computationally efficient. Results: This paper proposes and implements the LO ranking and retrieval algorithm based on the Tilted Time window and the Support Vector Machine, which uses the merit of both methods. The proposed model is implemented for the NCBI dataset and MAT Lab. Conclusion: The experiments have been carried out on the NCBI dataset, and LO weights are assigned to be relevant and non - relevant for a given user query according to the Tilted Time series and the Cosine similarity score. Results showed that the model proposed has much better accuracy.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

scholarly journals Randomized and Generated Instances Fitting with the Home Health Care Problem Subjected to Certain Constraints

2021 ◽  
Vol 11 (8) ◽  
pp. 3346
Author(s):  
Colin Huvent ◽  
Caroline Gagné ◽  
Aymen Sioud
Keyword(s):  
Health Care ◽  
Home Health Care ◽  
Hospital Cost ◽  
Time Window ◽  
Developed Countries ◽  
Home Health ◽  
Precedence Constraints ◽  
Social Organizations ◽  
Health Support ◽  
Time Window Constraints

Home Health Care (HHC) is a worldwide issue. It focuses on how medical and social organizations of different countries handle providing patients with health support at home. In most developed countries, reducing hospital cost constitutes a main objective. It is important to research the improvement of HHC logistics. This paper addressed the generation and development of a benchmark properly fitting different constraints of the HCC problem. Consequently, a generator was proposed dealing with all kinds of constraints such as time window constraints, workload constraints, synchronization, and precedence constraints. This generator allows researchers to validate and compare solving methods on a common dataset regardless of confidentiality issues. We validated our generator by firstly creating a common benchmark available for researchers and secondly by proposing a set of instances and a solving method based on an HHC problem found in the literature.

Parcel delivery cost minimization with time window constraints using trucks and drones

Networks ◽  
2021 ◽  
Author(s):  
Marc‐Antoine Coindreau ◽  
Olivier Gallay ◽  
Nicolas Zufferey
Keyword(s):  
Time Window ◽  
Cost Minimization ◽  
Delivery Cost ◽  
Time Window Constraints
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