Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications
Mathematical Problems in Engineering
; 2022, 2022.
Article
in English
| ProQuest Central | ID: covidwho-2064339
ABSTRACT
Transportation is regarded as one of the most important issues currently being researched;this issue needs the search for approaches or processes that might lessen many contemporary traffic concerns. Congestion, pollution, and accidents have escalated lately, negatively impacting urban environments, economic development, and citizens’ lifestyles. The rise of illnesses and epidemics throughout the world, such as COVID-19, has created an urgent need to find the best way to save people’s lives. The vehicle routing problem (VRP) is a well-known moniker for improving transportation systems and is regarded as one of the ancient and contemporary difficulties in route planning applications. One of the main tasks of VRP is serving many customers by determining the optimal route from an initial point to a destination on a real-time road map. The best route is not necessarily the shortest-distance route, but, in emergency cases, it is the route that takes the least fitness cost (time) and the fastest way to arrive. This paper aims to provide an adaptive genetic algorithm (GA) to determine the optimal time route, taking into account the factors that influence the vehicle arrival time and cause delays. In addition, the Network Analyst tool in ArcGIS is used to determine the optimal route using real-time map based on the user’s preferences and suggest the best one. Experimental results indicate that the performance of GA is mainly determined by an efficient representation, evaluation of fitness function, and other factors such as population size and selection method.
Engineering; Global positioning systems--GPS; Public transportation; Urban environments; Genetic algorithms; Mutation; Fitness; Route planning; Optimization; Roads & highways; Transportation planning; Maps; Chromosomes; Transportation systems; Traffic congestion; Algorithms; Route selection; Real time; Economic development; Adaptive algorithms
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Type of study:
Experimental Studies
Language:
English
Journal:
Mathematical Problems in Engineering
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS