  Task scheduling problem in heterogeneous systems is the process of allocating
tasks of an application to heterogeneous processors interconnected by
high-speed networks, so that minimizing the finishing time of application as
much as possible. Tasks are processing units of application and have
precedenceconstrained, communication and also, are presented by Directed
Acyclic Graphs (DAGs). Evolutionary algorithms are well suited for solving task
scheduling problem in heterogeneous environment. In this paper, we propose a
hybrid heuristic-based Artificial Immune System (AIS) algorithm for solving the
scheduling problem. In this regard, AIS with some heuristics and Single
Neighbourhood Search (SNS) technique are hybridized. Clonning and immune-remove
operators of AIS provide diversity, while heuristics and SNS provide
convergence of algorithm into good solutions, that is balancing between
exploration and exploitation. We have compared our method with some
state-of-the art algorithms. The results of the experiments show the validity
and efficiency of our method.
