Title: Web-Based Implementation of Travelling Salesperson Problem Using Genetic Algorithm,
Abstract: The world is connected through the Internet. As the abundance of Internet
users connected into the Web and the popularity of cloud computing research,
the need of Artificial Intelligence (AI) is demanding. In this research,
Genetic Algorithm (GA) as AI optimization method through natural selection and
genetic evolution is utilized. There are many applications of GA such as web
mining, load balancing, routing, and scheduling or web service selection.
Hence, it is a challenging task to discover whether the code mainly server side
and web based language technology affects the performance of GA. Travelling
Salesperson Problem (TSP) as Non Polynomial-hard (NP-hard) problem is provided
to be a problem domain to be solved by GA. While many scientists prefer Python
in GA implementation, another popular high-level interpreter programming
language such as PHP (PHP Hypertext Preprocessor) and Ruby were benchmarked.
Line of codes, file sizes, and performances based on GA implementation and
runtime were found varies among these programming languages. Based on the
result, the use of Ruby in GA implementation is recommended.