Hybrid Approach for the Public Transportation Time Dependent Orienteering Problem with Time Windows

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

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Yapay Arr Koloni Algoritmass ile Zaman Pencereli Takkm Oryantiring Problemlerinin zzmm (The Team Orienteering Problem with Time Windows by Using Artificial Bee Colony Algorithm)

SSRN Electronic Journal ◽

10.2139/ssrn.2509444 ◽

2014 ◽

Author(s):

Muhlis Ozdemir ◽

Mustafa Can

Keyword(s):

Artificial Bee Colony Algorithm ◽

Artificial Bee Colony ◽

Time Windows ◽

Orienteering Problem ◽

Team Orienteering Problem ◽

Bee Colony ◽

Team Orienteering

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Supervision of the Default Risk of Online Car-Hailing Platform from an Evolutionary Game Perspective

Sustainability ◽

10.3390/su13020555 ◽

2021 ◽

Vol 13 (2) ◽

pp. 555

Author(s):

Zhicheng Weng ◽

Pinliang Luo

Keyword(s):

Public Transportation ◽

Default Risk ◽

Control Mechanism ◽

Evolutionary Game ◽

Credit System ◽

Credit Constraint ◽

The Public ◽

Supervision Mode ◽

Public Transportation System ◽

Internal Supervision

Online car-hailing services are becoming a key component of the public transportation system, despite there being some certain risks, especially default risk. Turning to the evolutionary game method, this research constructed an evolutionary game model of online car-hailing platform, and then analyzed the equilibrium state of three scenarios (i.e., no supervision, internal supervision of platform enterprises, and external supervision of regulators), followed by carrying out a simulation. The results showed that to realize the evolution stability strategies (ESS) of default risk control, a strong credit constraint or the establishment of a coordinated supervision mode with appropriate intensity are needed. On this basis, this research puts forward the coordinated “platform enterprise + regulator” supervision mode, as well as the following four specific strategies: Promoting the construction of a credit system, strengthening the construction of laws and regulations, establishing a service process control mechanism, and introducing innovative regulatory means.

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Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

Discrete Dynamics in Nature and Society ◽

10.1155/2015/430109 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Sen Liu ◽

Zhilan Song ◽

Shuqi Zhong

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Public Transportation ◽

Group Decision ◽

Numerical Study ◽

Hub Location ◽

Hub Location Problem ◽

The Public ◽

Multiple Attribute ◽

Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

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