Performance comparison of discrete particle swarm optimisation and shuffled frog leaping algorithm in multiprocessor task scheduling problem

Abstract

Particle swarm optimisation (PSO) and Shuffled frog leaping (SFL) are Swarm Intelligence (SI) based algorithms. SI algorithms are stochastic based optimisation techniques that imitate process inspired from nature. This paper presents a comparative performance of two recent SI based optimisation algorithms such as discrete PSO (DPSO) and SFL in task scheduling problem. Task scheduling (TS) is a complex combinatorial optimisation problem and known to be NP-hard. It is an important challenging issue in distributed systems. Make span, mean flow time and reliability cost are performance criteria used to evaluate the efficiency of the DPSO and SFL algorithms for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the algorithms.