Publications
Code · Code Ocean · October 9, 2026
Density-Adaptive Locust Swarm Optimization for Cloud Workflow Scheduling
Abstract
This project presents a density-adaptive locust swarm optimization algorithm integrated with a self-supervised ordinary least squares warm-start mechanism, designed to optimize scientific workflow scheduling on public cloud infrastructures and achieve Pareto-optimal solutions by balancing performance, makespan, and operational costs.
Cloud Computing and Resource ManagementMetaheuristic Optimization Algorithms ResearchDistributed and Parallel Computing Systemscloud workflow schedulingscientific workflow schedulingordinary least squares
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