Paper #3

Performance of Parallel Distributed Bat Algorithm using MPI on a PC Cluster

Fazal Noor, Abdulghani Ibrahim and Mohammed M. AlKhattab

Abstract: Optimization algorithms are often used to obtain optimal solutions to complex nonlinear problems and appear in many areas such as control, communication, computation, and others. Bat algorithm is a heuristic optimization algorithm and efficient in obtaining approximate best solutions to non-linear problems. In many situations complex problems involve large amount of computations that may require simulations to run for days or weeks or even years for an algorithm to converge to a solution. In this research, a Parallel Distributed Bat Algorithm (PDBA) is formulated using Message Passing Interface (MPI) in C language code for a PC Cluster. The time complexity of PDBA is determined and presented. The performance in terms of speed-up, efficiency, elapsed time, and number of times fitness function is executed is also presented.

Keywords: Bat Algorithm; Computational Complexity; Distributed; Message Passing Interface (MPI); Optimization Algorithm; Parallel; PC Cluster; Neural Networks.