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The world is connected through the Internet. As the abundance of Internetusers 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 andgenetic evolution is utilized. There are many applications of GA such as webmining, load balancing, routing, and scheduling or web service selection.Hence, it is a challenging task to discover whether the code mainly server sideand web based language technology affects the performance of GA. TravellingSalesperson Problem (TSP) as Non Polynomial-hard (NP-hard) problem is providedto be a problem domain to be solved by GA. While many scientists prefer Pythonin GA implementation, another popular high-level interpreter programminglanguage such as PHP (PHP Hypertext Preprocessor) and Ruby were benchmarked.Line of codes, file sizes, and performances based on GA implementation andruntime were found varies among these programming languages. Based on theresult, the use of Ruby in GA implementation is recommended.

Web-Based Implementation of Travelling Salesperson Problem Using Genetic Algorithm