Smell Detection Agent Optimization Algorithm

SDA Optimization Algorithm (2014)

Smell Detection Agent (SDA) is an algorithm proposed by Vinod that employs canine trained behaviour. The algorithm creates a Cartesian space over a search space using smell trails and iterates the agents in resolving a path. The method can be applied to problems that incorporate path-based problems which are NP-hard.

Applications

• The algorithm is an intelligent multi-agent algorithm that can be used in any optimal path identification. This path should be the shortest path among all paths.
• Multi-objective optimization: Multiple SDAs with different smell capacities (modify the data structure) can be used to solve multi-objective optimization problems. Here the data structure plays an important role for recording the objectives. A multiple source-destination group can be handled by allowing more SDAs to solve the problem.
• Computer networking: The shortest path identification in a WAN link is possible by the SDA algorithm. Using the SDA algorithm, an optimised path is obtained in a multi-hop environment.
• SDN controllers: An SDA-based algorithm can be implemented in a controller for Software Defined Networking (SDN) with a method to identify multiple disjoint paths between source and destination nodes. SDN separates the control intelligence from the data packet transmission and uses the controller to dynamically recompute the network state based on availability.
• Subgraph networks: Subgraph identification is an important application in many sciences. The SDA algorithm is used for subgraph identification from a large complex network. This is especially in social media applications, drug discovery, protein-protein interaction and communication networks.

Bibliography

• Chandra S S, Vinod; Anand Hareendran (2020). Machine Learning: A Practitioner’s Approach. Prentice Hall. ISBN 978-93-893-4746-3. Archived from the original on 2020-10-16. Search this book on
• Chandra S S, Vinod; Anand Hareendran (2020). Artificial Intelligence: Principles and Applications. Prentice Hall. ISBN 978-93-893-4783-8. Archived from the original on 2020-10-10. Search this book on

References

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