A heuristic algorithm based on leaf photosynthate transport

SIMULATION ◽  
2017 ◽  
Vol 94 (7) ◽  
pp. 593-607 ◽  
Author(s):  
Yu Bin ◽  
Shan Wenxuan ◽  
Guo Zhen ◽  
Wang Yunpeng
Keyword(s):  
Network Design ◽  
Objective Function ◽  
Travel Time ◽  
Ant Colony Algorithm ◽  
Programming Model ◽  
Lower Layer ◽  
Transportation Network ◽  
Biological Evolution ◽  
Genetic Transmission ◽  
Total Travel Time

Transportation network design is non-deterministic polynomial-time hard due to its attributes of multi-objects, multi-constraints, and the non-convexity objective function. In this paper, a bi-level programming model is proposed for the transportation network design. The upper layer pursues the minimum total travel time of users and the total length of the road network simultaneously, while the lower layer is an equilibrium assignment model. A new algorithm for the network optimization based on the principle of leaf photosynthate transport in nature is proposed. The proposed algorithm simulates the natural selection of biological evolution and genetic transmission. It can retain the genetic idea of the evolutionary algorithm, together with the heuristic information update mechanism of swarm intelligence. Finally, empirical research is carried out with the Sioux Falls network to validate the performance of the proposed algorithm. The results show that although the total network length obtained by the proposed algorithm increases slightly compared with the ant colony algorithm and the genetic algorithm, the total travel time and objective function value reduce obviously. This indicates that the proposed algorithm has good performance on topology and efficiency.

scholarly journals Active Safety Planning Method for Transportation Network Design

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hongzhi Lin
Keyword(s):  
Network Design ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Programming Model ◽  
Transportation Network ◽  
Design Stage ◽  
Elite Strategy ◽  
Public Traffic ◽  
Total Travel Time ◽  
Bilevel Programming Model

Traffic accidents are frequent although various countermeasures are introduced. Traffic safety cannot be fundamentally improved if it is not considered in the transportation network design stage. Although it is well known that traffic safety is one of the most important concerns of the public, traffic safety is not adequately accommodated in transportation planning. This paper considers traffic safety as a major criterion in designing a transportation network. It is a kind of proactive measure rather than reactive measure. A bilevel programming model system is proposed where the upper level is the urban planners’ decision to minimize the estimated total number of traffic accidents, and the lower level is the travelers’ response behaviors to achieve transportation system equilibrium. A genetic algorithm (GA) with elite strategy is proposed to solve the bilevel model. The method of successive averages (MSA) is embedded for the lower level model, which is a feedback procedure between destination choice and traffic assignment. To demonstrate the effectiveness of the proposed method and algorithm, an experimental study is carried out. The results show that these methods can be a valuable tool to design a safer transportation network although efficiency, in terms of system total travel time, is slightly sacrificed.

scholarly journals Research on Road Traffic Network Design Model and Algorithm Considering Traffic Fairness

2021 ◽  
Vol 283 ◽  
pp. 02001
Author(s):  
SiWen Zhao
Keyword(s):  
Network Design ◽  
Travel Time ◽  
Road Network ◽  
Road Traffic ◽  
Programming Model ◽  
Network Design Problem ◽  
Traffic Network ◽  
Allocation Model ◽  
Total Travel Time ◽  
Traffic Network Design

Urban transportation is an important part of urban economic structure, which plays an important role in promoting the orderly development of society, residents' work and life. This paper analyzes the fairness in traffic network design problem, constructs the average network improvement index to measure fairness, and establishes a bi-level programming model for road traffic network design considering traffic fairness. The upper model includes the optimal total travel time and traffic fairness, and the lower model is the traffic flow allocation model. Then, according to the characteristics of the model, a genetic algorithm is designed to solve the model. Finally, a simple example is given to illustrate the effectiveness of the mathematical model and algorithm. The model proposed in this paper can get the final road design scheme satisfying the total travel time and traffic fairness of the road network under certain road network conditions, and can provide decision support for traffic planners.

Emergency Rescue Vehicle Dispatch Planning Using a Hybrid Algorithm

2018 ◽  
Vol 17 (06) ◽  
pp. 1865-1890 ◽  
Author(s):  
Jie Cao ◽  
He Han ◽  
Yi-Ping Jiang ◽  
Ya-Jing Wang
Keyword(s):  
Objective Function ◽  
Disaster Response ◽  
Hybrid Algorithm ◽  
Ant Colony Algorithm ◽  
Transportation Network ◽  
Mutation Operator ◽  
Nsga Ii ◽  
Emergency Rescue ◽  
Random Crossover ◽  
Crossover And Mutation

This paper describes the emergency rescue vehicle transportation network within the entire rescue period, and imitates rescue vehicle to select rescue route and to allocate emergency resource. The presented emergency rescue vehicle dispatch model seeks to minimize rescue time as the first objective function, minimize delay cost as the second objective function and maximize lifesaving utility as the last objective function in disaster response operations. To solve the proposed multiple objective model, a hybrid algorithm named nondominated sorting genetic algorithm (NSGA-II) with ant colony algorithm and a NSGA-II with random crossover and mutation, which can find better initial solution, are presented. In order to further prove the validity of the model and algorithm, a more complicated case is cited. Computational results are reported to illustrate the performance of the proposed model and algorithm. Statistical analysis confirms that the proposed random crossover and mutation operator outperforms the original crossover and mutation operator. The sensitivity analysis proves which parameter is more important for objective function values.

scholarly journals A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Haigen Min ◽  
Yukun Fang ◽  
Runmin Wang ◽  
Xiaochi Li ◽  
Zhigang Xu ◽  
...  
Keyword(s):  
Game Theory ◽  
Travel Time ◽  
Fuel Consumption ◽  
Transportation Network ◽  
Control Algorithms ◽  
Traffic Density ◽  
Automated Vehicles ◽  
Network Efficiency ◽  
Total Travel Time ◽  
The Cost

Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. In this paper, we focused on the scenario of on-ramp merging of CAVs, proposed a centralized approach based on game theory to control the process of on-ramp merging for all agents without any collisions, and optimized the overall fuel consumption and total travel time. For the framework of the game, benefit, loss, and rules are three basic components, and in our model, benefit is the priority of passing the merging point, represented via the merging sequence (MS), loss is the cost of fuel consumption and the total travel time, and the game rules are designed in accordance with traffic density, fairness, and wholeness. Each rule has a different degree of importance, and to get the optimal weight of each rule, we formulate the problem as a double-objective optimization problem and obtain the results by searching the feasible Pareto solutions. As to the assignment of merging sequence, we evaluate each competitor from three aspects by giving scores and multiplying the corresponding weight and the agent with the higher score gets comparatively smaller MS, i.e., the priority of passing the intersection. The simulations and comparisons are conducted to demonstrate the effectiveness of the proposed method. Moreover, the proposed method improved the fuel economy and saved the travel time.

Network Design for Shipping Service of Large-Scale Intermodal Liners

2012 ◽  
Vol 2269 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Liner Shipping ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Hub And Spoke ◽  
Shipping Company ◽  
Proposed Model

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.

scholarly journals Mixed Transportation Network Design under a Sustainable Development Perspective

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jin Qin ◽  
Ling-lin Ni ◽  
Feng Shi
Keyword(s):  
Sustainable Development ◽  
Network Design ◽  
Programming Model ◽  
Transportation Network ◽  
Exhaust Emissions ◽  
Network Design Problem ◽  
Projection Algorithm ◽  
Vehicle Exhaust ◽  
Decision Variables ◽  
Bilevel Programming Model

A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%.

Identifying Critical Links in Transportation Network Design Problems for Maximizing Network Accessibility

2020 ◽  
Vol 2674 (2) ◽  
pp. 237-251
Author(s):  
Yufeng Zhang ◽  
Alireza Khani
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Time Budget ◽  
Relaxation Method ◽  
Design Problems ◽  
Network Design Problems ◽  
Critical Links ◽  
Travel Time Budget

A significant amount of research has been performed on network accessibility evaluation, but studies on incorporating accessibility maximization into network design problems have been relatively scarce. This study aimed to bridge the gap by proposing an integer programming model that explicitly maximizes the number of accessible opportunities within a given travel time budget. We adopted the Lagrangian relaxation method for decomposing the main problem into three subproblems that can be solved more efficiently using dynamic programming. The proposed method was applied to several case studies, which identified critical links for maximizing network accessibility with limited construction budget, and also illustrated the accuracy and efficiency of the algorithm. This method is promisingly scalable as a solution algorithm for large-scale accessibility-oriented network design problems.

Sales Territory Alignment to Maximize Profit

1975 ◽  
Vol 12 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Leonard M. Lodish
Keyword(s):  
Mathematical Programming ◽  
Objective Function ◽  
Travel Time ◽  
Programming Model ◽  
Solution Procedure ◽  
Sales Force ◽  
Mathematical Programming Model ◽  
Heuristic Solution ◽  
Frequency Determination ◽  
Unique Model

A mathematical programming model and heuristic solution procedure are developed to realign sales territories. Unique model aspects are: (1) the objective function is the anticipated profit generated by the sales force; (2) the interrelated problem of account specific call frequency determination is simultaneously considered; (3) travel time is considered, including combining calls on accounts into trips.

Multi-Objective Optimization for Skip-Stop Strategy Based on Smartcard Data Considering Total Travel Time and Equity

2021 ◽  
pp. 036119812110130
Author(s):  
Sang-Wook Han ◽  
Eun Hak Lee ◽  
Dong-Kyu Kim
Keyword(s):  
Travel Time ◽  
Programming Model ◽  
Mixed Integer ◽  
Average Deviation ◽  
Multi Objective ◽  
Nonlinear Programming Model ◽  
Total Travel Time ◽  
Transfer Stations ◽  
The City

With the rise of urban sprawl, urban railways extend out further to the city’s outer district, installing additional stations. Passengers who travel from the outer district to the center of the city therefore experience long travel times. Although skip-stop strategy helps save total travel time, deviation of travel time among all origin–destination pairs may be increased, leading to equity problems. This study aims to minimize the inequity and total travel time through train stop planning and train scheduling. A coefficient of variation is adopted as a measure of inequity. The problem is formulated as a multi-objective mixed integer nonlinear programming model. Origin–destination demand is extracted from smartcard data and a case study of four urban railway lines in Seoul is conducted. The results indicate that the number of transfer stations for equity-oriented skip-stop strategy is smaller than that for total-travel-time-oriented skip-stop strategy. We also discover that as the number of transfer stations rises, inequity increases and total travel time is reduced. For skip-stop strategy considering total travel time and equity simultaneously, average total travel time and the average deviation are reduced by up to 10.3% and 10.6%, respectively, compared with those of all-stop strategy. We analyze the gradient of Pareto optimal sets to find out which factors (equity or total travel time) are more significant. Skip-stop strategy on lines 5 and 9 can be designed based on equity, while line 4 can be planned based on total travel time.

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