scholarly journals Sensor Location Problem for Network Traffic Flow Derivation Based on Turning Ratios at Intersection

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Minhua Shao ◽  
Lijun Sun ◽  
Xianzhi Shao
Keyword(s):  
Network Flow ◽  
Location Problem ◽  
Optimal Solution ◽  
Coefficient Matrix ◽  
Sensor Location ◽  
The Road ◽  
Minimum Number ◽  
Flow Conservation ◽  
The Greedy Algorithm ◽  
Counting Points

The sensor location problem (SLP) discussed in this paper is to find the minimum number and optimum locations of the flow counting points in the road network so that the traffic flows over the whole network can be inferred uniquely. Flow conservation system at intersections is formulated firstly using the turning ratios as the prior information. Then the coefficient matrix of the flow conservation system is proved to be nonsingular. Based on that, the minimal number of counting points is determined to be the total number of exclusive incoming roads and dummy roads, which are added to the network to represent the trips generated on real roads. So the task of SLP model based on turning ratios is just to determine the optimal sensor locations. The following analysis in this paper shows that placing sensors on all the exclusive incoming roads and dummy roads can always generate a unique network flow vector for any network topology. After that, a detection set composed of only real roads is proven to exist from the view of feasibility in reality. Finally, considering the roads importance and cost of the sensors, a weighted SLP model is formulated to find the optimal detection set. The greedy algorithm is proven to be able to provide the optimal solution for the proposed weighted SLP model.

The Location Problem of Given and Indivisible Different Units

1970 ◽  
Vol 2 (3) ◽  
pp. 341-356
Author(s):  
G. Jándy
Keyword(s):  
Exact Solution ◽  
Heuristic Algorithm ◽  
Network Flow ◽  
Location Problem ◽  
Optimal Solution ◽  
Type Problem ◽  
Distribution Problem ◽  
Enumeration Algorithm ◽  
Weighted Distribution ◽  
Partial Enumeration

In cases where certain simplifications are allowed, the location optimisation of given and indivisible different economic units may be modelled as a bi-value weighted distribution problem. The paper presents a heuristic algorithm for this network-flow-type problem and also a partial enumeration algorithm for deriving the exact solution. But it is also pointed out that an initial sub-optimal solution can quickly be improved with a derivation on a direct line only, if the exact solution is not absolutely essential. A numerical example is used to illustrate the method of derivation on a direct line starting with an upper bound given by a sub-optimal solution.

scholarly journals Optimization Model for the Supply Volume of Bike-Sharing: Case Study in Nanjing, China

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 182
Author(s):  
Jiajie Yu ◽  
Yanjie Ji ◽  
Chenyu Yi ◽  
Chenchen Kuai ◽  
Dmitry Ivanovich Samal
Keyword(s):  
Optimization Model ◽  
Road Network ◽  
Optimal Solution ◽  
Traffic Analysis ◽  
Urban Traffic ◽  
Mixed Integer ◽  
The Road ◽  
Bike Sharing ◽  
Flow Conservation ◽  
Parking Facilities

In order to solve the oversupply and repositioning problems of bike-sharing, this paper proposes an optimization model to obtain a reasonable supply volume scheme for bike-sharing and infrastructure configuration planning. The optimization model is constrained by the demand for bike-sharing, urban traffic carrying capacity (road network and parking facilities carrying capacities), and the flow conservation of shared bikes in each traffic analysis zone. The model was formulated through mixed-integer programming with the aim of minimizing the total costs for users and bike-sharing enterprises (including the travel cost of users, production and maintenance costs of shared bikes, and repositioning costs). CPLEX was used to obtain the optimal solution for the model. Then, the optimization model was applied to 183 traffic analysis zones in Nanjing, China. The results showed that not only were user demands met, but the load ratios of the road network and parking facilities with respect to bike-sharing in each traffic zone were all decreased to lower than 1.0 after the optimization, which established the rationality and effectiveness of the optimization results.

Optimal Time Interval for Investigating Prior Information in Network Sensor Location Problem

2020 ◽  
pp. 036119812096882
Author(s):  
Congcong Xie ◽  
Minhua Shao
Keyword(s):  
Traffic Flow ◽  
Prior Information ◽  
Location Problem ◽  
Early Morning ◽  
Optimal Time ◽  
Time Interval ◽  
Sensor Location ◽  
Flow Information ◽  
Minimum Number ◽  
Flow Of Information

Based on various types of prior information, the network sensor location problem (NSLP) optimizes the locations of sensors in a network, providing comprehensive traffic flow information with a minimum number of sensors. However, few studies have considered the accuracy of prior information, and it is obvious that prior information inconsistent with reality will affect the results of NSLP. Generally, prior information can be obtained from other flow information. When solving NSLP, prior information requires additional or specialized field flow investigations to ensure its accuracy. In general, short-term prior information is adopted to infer the flow of information of interest. The purpose of this study is, therefore, to select the optimal time interval for investigating prior information. This study analyzed the types and characteristics of prior information, and proposed a mathematical method based on Pareto Optimality to identify the optimal time interval for investigating prior information, which can not only ensure the accuracy of prior information, but also reduce the investigation cost. Taking the turning ratio as an example, the traffic flow collected by sensors located at nine intersections on Zhongshan North Road in Shanghai, China was analyzed, and the turning ratios were calculated. Using the proposed method, the optimal time interval for investigating the turning ratio was determined to be 20 to 25 min. In addition, the most representative time intervals were identified as 9:00 to 10:00 a.m. It is recommended that investigating prior information in the early morning and in the morning and evening peaks be avoided.

scholarly journals Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 934
Author(s):  
Mariacrocetta Sambito ◽  
Gabriele Freni
Keyword(s):  
Treatment Plant ◽  
Optimal Solution ◽  
Monitoring Network ◽  
Computational Effort ◽  
Bayesian Optimization ◽  
Urban Drainage ◽  
Optimization Approach ◽  
Sensor Location ◽  
Contamination Source ◽  
Monitoring Point

In the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network nodes to have equal possibilities to allocate a sensor. In the present study, such a common approach is compared with different initial strategies to pre-screen eligible nodes as a function of topological and hydraulic information, and non-formal 'grey' information on the most probable locations of the contamination source. Such strategies were previously compared for conservative xenobiotic contaminations and now they are compared for a more difficult identification exercise: the detection of nonconservative immanent contaminants. The strategies are applied to a Bayesian optimization approach that demonstrated to be efficient in contamination source location. The case study is the literature network of the Storm Water Management Model (SWMM) manual, Example 8. The results show that the pre-screening and ‘grey’ information are able to reduce the computational effort needed to obtain the optimal solution or, with equal computational effort, to improve location efficiency. The nature of the contamination is highly relevant, affecting monitoring efficiency, sensor location and computational efforts to reach optimality.

Study and Analysis of GA-Based Heuristic Applied to Assembly Line Balancing Problem

2014 ◽  
Vol 13 (02) ◽  
pp. 113-131 ◽  
Author(s):  
P. Sivasankaran ◽  
P. Shahabudeen
Keyword(s):  
Cycle Time ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Optimal Solution ◽  
Vital Role ◽  
Line Balancing ◽  
Problem Size ◽  
Minimum Number ◽  
Assembly Line Balancing Problem ◽  
Balancing Efficiency

Balancing assembly line in a mass production system plays a vital role to improve the productivity of a manufacturing system. In this paper, a single model assembly line balancing problem (SMALBP) is considered. The objective of this problem is to group the tasks in the assembly network into a minimum number of workstations for a given cycle time such that the balancing efficiency is maximized. This problem comes under combinatorial category. So, it is essential to develop efficient heuristic to find the near optimal solution of the problem in less time. In this paper, an attempt has been made to design four different genetic algorithm (GA)-based heuristics, and analyze them to select the best amongst them. The analysis has been carried out using a complete factorial experiment with three factors, viz. problem size, cycle time, and algorithm, and the results are reported.

scholarly journals FLOW OVER TIME PROBLEM WITH INFLOW-DEPENDENT TRANSIT TIMES

2018 ◽  
Vol 23 (1) ◽  
pp. 49-56
Author(s):  
Durga Prasad Khanal ◽  
Urmila Pyakurel ◽  
Tanka Nath Dhamala
Keyword(s):  
Network Flow ◽  
Time Horizon ◽  
The Road ◽  
Transit Times ◽  
Time Problem ◽  
Fast Flow ◽  
Static Flow ◽  
Time Expanded Network ◽  
Flow Over Time ◽  
Over Time

 Network flow over time is an important area for the researcher relating to the traffic assignment problem. Transmission times of the vehicles directly depend on the number of vehicles entering the road. Flow over time with fixed transit times can be solved by using classical (static) flow algorithms in a corresponding time expanded network which is not exactly applicable for flow over time with inflow dependent transit times. In this paper we discuss the time expanded graph for inflow-dependent transit times and non-existence of earliest arrival flow on it. Flow over time with inflow-dependent transit times are turned to inflow-preserving flow by pushing the flow from slower arc to the fast flow carrying arc. We gave an example to show that time horizon of quickest flow in bow graph GB was strictly smaller than time horizon of any inflow-preserving flow over time in GB satisfying the same demand. The relaxation in the modified bow graph turns the problem into the linear programming problem.

scholarly journals Controllability of Flow-Conservation Transportation Networks with Fractional-Order Dynamics

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Chen ◽  
Bo Zhou
Keyword(s):  
Theoretical Analysis ◽  
Fractional Derivative ◽  
Exact Solutions ◽  
Fractional Order ◽  
Location Problem ◽  
Transportation Networks ◽  
Qr Decomposition ◽  
Rank Condition ◽  
Numerical Examples ◽  
Flow Conservation

In this paper, we adapt the fractional derivative approach to formulate the flow-conservation transportation networks, which consider the propagation dynamics and the users’ behaviors in terms of route choices. We then investigate the controllability of the fractional-order transportation networks by employing the Popov-Belevitch-Hautus rank condition and the QR decomposition algorithm. Furthermore, we provide the exact solutions for the full controllability pricing controller location problem, which includes where to locate the controllers and how many controllers are required at the location positions. Finally, we illustrate two numerical examples to validate the theoretical analysis.

scholarly journals Minimum Cell Connection in Line Segment Arrangements

2017 ◽  
Vol 27 (03) ◽  
pp. 159-176
Author(s):  
Helmut Alt ◽  
Sergio Cabello ◽  
Panos Giannopoulos ◽  
Christian Knauer
Keyword(s):  
Linear Time ◽  
Optimal Solution ◽  
Time Algorithm ◽  
Linear Time Algorithm ◽  
Constant Number ◽  
Line Segments ◽  
Straight Line ◽  
Minimum Number ◽  
Number Of Segments ◽  
Connection Problems

We study the complexity of the following cell connection problems in segment arrangements. Given a set of straight-line segments in the plane and two points [Formula: see text] and [Formula: see text] in different cells of the induced arrangement: [(i)] compute the minimum number of segments one needs to remove so that there is a path connecting [Formula: see text] to [Formula: see text] that does not intersect any of the remaining segments; [(ii)] compute the minimum number of segments one needs to remove so that the arrangement induced by the remaining segments has a single cell. We show that problems (i) and (ii) are NP-hard and discuss some special, tractable cases. Most notably, we provide a near-linear-time algorithm for a variant of problem (i) where the path connecting [Formula: see text] to [Formula: see text] must stay inside a given polygon [Formula: see text] with a constant number of holes, the segments are contained in [Formula: see text], and the endpoints of the segments are on the boundary of [Formula: see text]. The approach for this latter result uses homotopy of paths to group the segments into clusters with the property that either all segments in a cluster or none participate in an optimal solution.

Application of the optimal network flow method to the problem of locomotive selection for freight trains on the Eastern Polygon

2019 ◽  
pp. 94-106
Author(s):  
Александр Борисович Шабунин ◽  
Андрей Куркенович Такмазьян
Keyword(s):  
Network Flow ◽  
Optimal Solution ◽  
Global Optimum ◽  
Full Scale ◽  
Scale Model ◽  
Test Cases ◽  
Processor Time ◽  
Flow Method ◽  
Optimal Network ◽  
Locomotive Assignment

Моделируется подбор тяговых ресурсов (локомотивов - в данном случае) для провоза грузовых поездов. В качестве входных данных рассматриваются маршрут поезда, время готовности поезда к отправлению, средняя скорость и вес поезда. Имеется множество локомотивов, обладающих грузоподъемностью и областью разрешенного действия. Цель - оптимально подобрать ресурс для каждого участка маршрута поезда. Решение ищется методом потока ресурсов минимальной суммарной стоимости через специально сконструированную сеть. Сеть построена на основе взвешенного орграфа из ребер графика поездов на линейных участках и ребер альтернативы, в процессе прохода по которым осуществляется “смена деятельности” локомотива (например, отцепление от одного поезда и подцепка к другому). Полученное решение обладает свойством глобальной оптимальности по времени. The selection of traction resources (locomotives) for the transport of freight trains is modelled. The input data are the train route, the readiness time of the train for departure, the average speed and weight of the train. In addition, there are many locomotives with a carrying capacity and an area of permitted action. The research objective is to optimally select a resource for each segment of the train route. The solution is sought by the resource flow method of the minimum total cost through a specially designed network. The network includes edges created from train schedule segments whose filling means locomotive assignment to train at the segment, and special alternative edges, passing through which a locomotive alternates its assignment. The algorithm for finding the optimal solution is the method of pushing through the pre-flow proposed by A. Goldberg and R. Tarjan. This is one of the fastest algorithms converging to a global optimum. Two test cases were investigated: a trivial one, out of six trains and three locomotives, and a more complicated one, which is a model example the size of 10% of the full scale model and consists of 150 trains. Full scale calculations provide planning of the freight transportation on the Eastern Operational domain of the Russian Railways. The model includes 1800 locomotives and about 3000 trains on the time horizon of 48 hours. Solution is found in less than 5 minutes of processor time for a PC powered by Intel(R) Pentium(R) G2010 2.80 GHz processor.

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