A Hybrid Multi‐Objective Algorithm With IWOA ‐Inspired Dispersal for Task Scheduling in IaaS

ABSTRACT

Cloud task scheduling in IaaS environments often suffers from long makespan, high execution cost, and slow convergence. To address this problem, this paper proposes a hybrid multi‐objective algorithm with IWOA‐inspired dispersal (HMOA‐ID). An adaptive crossover controller and a group‐based optimization mechanism are incorporated to enhance search robustness. In addition, a modified crowding strategy is introduced to jointly preserve objective‐space diversity and decision‐space diversity, thereby improving the quality of the obtained Pareto solutions. Experimental results on benchmark task scheduling instances show that HMOA‐ID achieves competitive and stable performance compared with several representative multi‐objective optimization algorithms.