A. Daneshvar

Combined approach for task scheduling in cloud computing systems using meta-heuristic algorithms and virtual machine migration

This study aims to optimize task scheduling systems in cloud computing environments by leveraging efficient meta-heuristic algorithms to maximize hardware efficiency, minimize space utilization, and reduce maintenance costs. Cloud computing has emerged as a new information technology platform beyond traditional inf...

Multi-Objective Optimization of Closed-Loop Supply Chains in the Automotive Industry: Integrating Financial and Material Flows

Designing a cloud logistics mathematical model for photovoltaic systems using a metaheuristic algorithm

A novel cloud logistics model for SPV systems is proposed by integrating deep learning with metaheuristic optimization, particularly NSGA-II, to improve supply, distribution and energy management decisions in photovoltaic supply chains and is validated across different problem scales.