A Survey Paper on Solving TSP using Ant Colony Optimization on GPU

Authors

  • Khatri K Student in ME (CSE) at Hasmukh Goswami College Of Engineering, Ahmedabad, India
  • Gupta VK Professor in Computer Dept, Hasmukh Goswami College Of Engineering, Ahmedabad, India

Keywords:

Ant Colony Optimization, TSP, GPU, CUDA Architecture, Parallel Implementation

Abstract

Ant Colony Optimization (ACO) is meta-heuristic algorithm inspired from nature to solve many combinatorial optimization problem such as Travelling Salesman Problem (TSP). There are many versions of ACO used to solve TSP like, Ant System, Elitist Ant System, Max-Min Ant System, Rank based Ant System algorithm. For improved performance, these methods can be implemented in parallel architecture like GPU, CUDA architecture. Graphics Processing Unit (GPU) provides highly parallel and fully programmable platform. GPUs which have many processing units with an off-chip global memory can be used for general purpose parallel computation. This paper presents a survey on different solving TSP using ACO on GPU.

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Published

2024-02-26

How to Cite

Khatri, K., & Gupta, V. K. (2024). A Survey Paper on Solving TSP using Ant Colony Optimization on GPU. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(12), 1354–1359. Retrieved from https://ijact.in/index.php/j/article/view/234

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Section

Original Research Article

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