Approach to Find Shortest Path Using Ant Colony Algorithm

  • Mudasar Basha
  • M. Siva Kumar
  • Vemulapalli Sai Pranav
  • B. Khaleelu Rehman
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 624)


This paper deals with Ant Colony Optimization (ACO). Our approach is to compare the run-time and accuracy of existing techniques using Ant Colony Optimization to find the shortest path. Here, we are going to study how to locate the shortest path using Dijkstra’s, Bellman–Ford and Kruskal’s algorithms, and comparisons will be done among all the algorithms. Ant lays pheromone on the path it travelled to identify the shortest path from its nest to the food source. We will also be studying what are the uses of implementing ACO algorithm on a XILINX ZYNQ-7000 PSoC (Programmable System on Chip) instead of implementing it on Arduino or Raspberry Pi.


Ant Colony Optimization (ACO) Dijkstra’s algorithm Bellman–Ford algorithm Kruskal’s algorithm Pheromone Xilinx ZYNQ-7000 PSoC 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Mudasar Basha
    • 1
  • M. Siva Kumar
    • 2
  • Vemulapalli Sai Pranav
    • 1
  • B. Khaleelu Rehman
    • 3
  1. 1.Department of ECEBVRIT-NHyderabadIndia
  2. 2.Department of ECEK L UniversityVijayawadaIndia
  3. 3.Department of Electronics, Instrumentation & Control EngineeringUniversity of Petroleum & Energy StudiesDehradunIndia

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