Real-Time Task Scheduling Using Hybrid Multi-objective Crow Search Algorithm

Abstract

This paper proposes a Multi-objective Crow Search Algorithm (MOCSA) based task scheduling approach for determining optimal solutions with simultaneous optimization of finish time (F), tardiness (T) and energy consumption (E). The proposed algorithm solves real-time task scheduling problem in heterogeneous multi-processor systems by adopting novel crow search algorithm to solve the discrete optimization problem. The three different multiple objectives with different magnitudes are fused using a weighted product method. Our methodology enables the user to choose the solution that best suits their needs. Experimental results demonstrate the efficiency of the proposed algorithm in achieving all the three objectives: minimizing finish time, tardiness and energy consumption.