Parallel EigenAnt algorithm based on MPI by ACO Approach
Paper ID : 1174-ICTCK (R4)
1نجمه دامغانی *, 2وحید ستاری نائینی
1دانشگاه پیام نور واحد بم
2عضو هیئت علمی دانشگاه شهید باهنر کرمان
Parallelization is among the best approaches that can be used to enhance the performance in heuristic algorithms. The EigenAnt algorithm model is an Ant Colony Optimization (ACO) that leads to the selection of the shortest paths. In this research, we propose a Parallel EigenAnt Algorithm (PEAA) using Ant Colony Optimization approach. The algorithm is implemented by Message Passing Interface (MPI) in a parallel form. It is possible to send or receive messages to a group of processes in collective communications. Parallel EigenAnt algorithm improves the speed to find a better solution by ants. Experimental results showed that the proposed parallel EigenAnt algorithm yields a significant improvement by finding the shortest path from a source to a destination. The results also showed that the suggested algorithm improves the execution time and efficiency. The performance of the proposed method improved the speedup, efficiency and quality of solution compared to Sequential EigenAnt algorithm.
Ant Colony Optimization, Parallel Computing, EigenAnt Algorithm, Message Passing Interface
Status : Paper Accepted