On the Method of Ship’s Transoceanic Route Planning

2011 ◽  
pp. 157-163 ◽  
Author(s):  
O Pipchenko
Keyword(s):  
Route Planning

Tourism Route Planning Route Based on Tourist Category using Orientee ring Problem with Time Windows

2019 ◽  
Vol 1 (1) ◽  
pp. 42-49
Author(s):  
Indri Hapsari ◽  
◽  
Hazrul Is wadi ◽  
Yosvaldo Ongko Cahyadi ◽  
◽  
...  
Keyword(s):  
Time Windows ◽  
Route Planning ◽  
Ring Problem

Recent advances on urban taxi sharing systems with the path arrival probability

2020 ◽  
Vol 13 ◽  
Author(s):  
Dui Hongyan ◽  
Zhang Chi
Keyword(s):  
Failure Probability ◽  
Traffic Congestion ◽  
Optimal Strategy ◽  
Time Windows ◽  
Optimal Path ◽  
Route Planning ◽  
Driving Time ◽  
Load Rate ◽  
Travel Efficiency ◽  
Arrival Probability

Background : Taxi sharing is an emerging transportation arrangement that helps improve the passengers’ travel efficiency and reduce costs. This study proposes an urban taxi sharing system. Methods: Considering each side congestion of the transport network, their corresponding reliability and failure probability are analyzed. Under the constraints of the number of passengers and their own time windows, the analysis is performed on passengers whose optimal path is inclusive. Results: According to the optimal strategy, the different passengers can be arranged into the same taxi to realize the taxi sharing. Then the shared taxi route can be optimized. Conclusion: Due to the reasonable vehicle route planning and passenger combination, these can effectively alleviate the traffic congestion, save the driving time, reduce the taxi no-load rate, and save the driving distance. At last, a numerical example is used to demonstrate the proposed method.

A distributed location obfuscation method for online route planning

2020 ◽  
Vol 95 ◽  
pp. 101850
Author(s):  
Padraig Corcoran ◽  
Peter Mooney ◽  
Andrei Gagarin
Keyword(s):  
Route Planning ◽  
Location Obfuscation

Toward Greater Intelligence in Route Planning: A Graph-Aware Deep Learning Approach

2020 ◽  
Vol 14 (2) ◽  
pp. 1658-1669 ◽  
Author(s):  
Zirui Zhuang ◽  
Jingyu Wang ◽  
Qi Qi ◽  
Haifeng Sun ◽  
Jianxin Liao
Keyword(s):  
Deep Learning ◽  
Route Planning ◽  
Learning Approach

scholarly journals Tourist Route Optimization in the Context of Covid-19 Pandemic

2021 ◽  
Vol 13 (10) ◽  
pp. 5492
Author(s):  
Cristina Maria Păcurar ◽  
Ruxandra-Gabriela Albu ◽  
Victor Dan Păcurar
Keyword(s):  
Travelling Salesman Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Travelling Salesman ◽  
Social Distancing ◽  
Tourist Destinations ◽  
Innovative Method ◽  
The Social ◽  
Immediate Response

The paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer one in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

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