Heuristic algorithms for scheduling multi-layer computer systems

Abstract

Multi-layer multiprocessor systems are generally employed in real-time applications such as robotics and computer vision. The authors developed three efficient heuristic scheduling algorithms for such systems. In their model, they considered scheduling multiprocessor tasks with arbitrary processing times and arbitrary processor requirements in a two-stage hybrid flow-shop to minimize makespan. They also derived an effective lower bound for the problem. Then, they analyzed the average performance of the heuristic algorithms by computing the average percentage deviation of each heuristic solution from the lower bound. The results of the computational experiment to test the average performance of the proposed heuristic algorithms on a set of randomly generated problems showed that the proposed heuristic algorithms perform well.