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.

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

2021 ◽  
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 be an important advantage in transforming a destination into a safer destination 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 to the spotlight the issue of overcrowded attractions inside a destination at certain moments. The method proposed in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented aims to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating the social distancing measures imposed by Covid-19.

scholarly journals SCAN PLANNING AND ROUTE OPTIMIZATION FOR CONTROL OF EXECUTION OF AS-DESIGNED BIM

2018 ◽  
Vol XLII-4 ◽  
pp. 143-148 ◽  
Author(s):  
L. Díaz-Vilariño ◽  
E. Frías ◽  
J. Balado ◽  
H. González-Jorge
Keyword(s):  
Optimization Algorithm ◽  
Point Cloud ◽  
Processing Time ◽  
Travelling Salesman Problem ◽  
Route Optimization ◽  
Optimal Route ◽  
Ant Colony Optimization Algorithm ◽  
Travelling Salesman ◽  
Tracing Algorithm ◽  
Grid Based

<p><strong>Abstract.</strong> Scan-to-BIM systems have been recently proposed for the dimensional and quality assessment of as-built construction components with planned works. The procedure is generally based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models. A major concern in Scan-to-BIM procedures is point cloud quality in terms of data completeness and consequently, the scanning process should be designed in order to obtain a full coverage of the scene while avoiding major occlusions. This work proposes a method to optimize the number and scan positions for Scan-to-BIM procedures following stop &amp;amp; go scanning. The method is based on a visibility analysis using a <i>ray-tracing algorithm</i>. In addition, the optimal route between scan positions is formulated as a <i>travelling salesman problem</i> and solved using a suboptimal <i>ant colony optimization algorithm</i>. The distribution of candidate positions follows a grid-based structure, although other distributions based on triangulation or tessellation can be implemented to reduce the number of candidate positions and processing time.</p>

scholarly journals Location flexibility in parcel delivery operations: framework and empirical analysis

2021 ◽  
Author(s):  
Dmitry Krushinsky ◽  
Xuezhen Guo ◽  
G D H Claassen
Keyword(s):  
Vehicle Routing ◽  
Empirical Analysis ◽  
Travelling Salesman Problem ◽  
Daily Practice ◽  
Route Optimization ◽  
Computational Experiments ◽  
Travelling Salesman ◽  
Route Length ◽  
Flexible Delivery

Abstract In traditional parcel delivery operations, customers determine delivery locations and, hence, the performance of a transporter. We exploit this idea and show that customers can improve the efficiency of a transporter by giving the latter flexibility in choosing the delivery locations. Two possible policies to enable this flexibility are presented and evaluated. The first policy, conceptually similar to roaming vehicle routing, is related to the presence of alternative locations. The second policy is related to the possibility of aggregating/skipping some locations. We show that route optimization behind both policies can be modelled via the well-known generalized travelling salesman problem. Extensive computational experiments with real parcel delivery data are performed to evaluate the potential of the presented policies and to obtain insights for possible implementation in daily practice. The experiments show that under certain conditions, the two proposed policies can lead to 15 to 20% improvement in the route length and in extreme yet realistic cases up to 40 to 50%. Consequently, the concept of flexible delivery locations has potential for practice, especially in densely populated areas.

scholarly journals Implementation of Genetic Algorithm to Solving Travelling Salesman Problem with Time Window (TSP-TW) for Scheduling Tourist Destinations in Malang City

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Gusti Eka Yuliastuti ◽  
Wayan Firdaus Mahmudy ◽  
Agung Mustika Rizki
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Travelling Salesman Problem ◽  
Optimal Scheduling ◽  
Test Results ◽  
Travelling Salesman ◽  
Tourist Destinations ◽  
Fitness Value ◽  
Time Window Constraints ◽  
Test Result

In doing travel to some destinantions, tourist certainly want to be able to visit many destinations with the optimal scheduling so that necessary in finding the best route and not wasting lots of time travel. Several studies have addressed the problem but does not consider other factor which is very important that is the operating hours of each destination or hereinafter referred as the time window. Genetic algorithm proved able to resolve this travelling salesman problem with time window constraints. Based on test results obtained solutions with the fitness value of 0,9856 at the time of generation of 800 and the other test result obtained solution with the fitness value of 0,9621 at the time of the combination CR=0,7 MR=0,3.

scholarly journals An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 58 ◽  
Author(s):  
Kshitij Srivastava ◽  
Prem Chandra Pandey ◽  
Jyoti K. Sharma
Keyword(s):  
Precision Agriculture ◽  
Travelling Salesman Problem ◽  
Optimal Path ◽  
Route Planning ◽  
Route Optimization ◽  
Crop Fields ◽  
Effective Dispersion ◽  
Agricultural Applications ◽  
Stressed Region ◽  
Network Software

This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the task without a revisit, one needs to employ optimized routes and optimal points of delivering the inputs required in precision agriculture (PA). First, stressed regions are identified using VegNet (Vegetative Network) software. Then, methods are applied for obtaining optimal routes and points for the spraying of inputs with an autonomous UAV for PA. This paper reports a unique and innovative technique to calculate the optimum location of spray points required for a particular stressed region. In this technique, the stressed regions are divided into many circular divisions with its center being a spray point of the stressed region. These circular divisions would ensure a more effective dispersion of the spray. Then an optimal path is found out which connects all the stressed regions and their spray points. The paper also describes the use of methods and algorithms including travelling salesman problem (TSP)-based route planning and a Voronoi diagram which allows applying precision agriculture techniques.

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