Abstract
Intelligent water drops (IWD) algorithm is a new meta-heuristic approach belonging to a class of swarm intelligence-based algorithms. It is inspired from observing processes of natural water swarm that happen in the natural river systems. This paper presents an improved IWD algorithm based on developing an adaptive schema to prevent the IWD algorithm from premature convergence. The performance of the adaptive IWD is compared with original IWD and other meta-heuristic algorithms in solving travelling salesman problem (TSP). The results clearly show that the proposed algorithm has better performance than those of original IWD, and MIWD-TSP algorithm and very competitive results to others meta-heuristics.
Original language | English |
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Pages (from-to) | 103-111 |
Number of pages | 9 |
Journal | International Journal of Bio-Inspired Computation |
Volume | 3 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2011 |
Keywords
- Adaptive intelligent water drops
- Intelligent water drops
- IWD
- Meta-heuristic approach
- MIWD-TSP
- Modified IWD for TSP
- Swarm intelligence
- Travelling salesman problem
- TSP
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science