Multiobjective Optimization for Multi-UAV-Assisted MEC Systems
Abstract
Internet of Things (IoT) task offloading involves conflicting objectives of energy consumption and delay. We formulate a bi-objective optimization model for a multi-UAV-assisted mobile edge computing (MEC) system, jointly optimizing resource allocation, task offloading decisions, and UAV deployment to minimize both energy consumption and delay. As the number of offloaded tasks increases, finding feasible solutions becomes more challenging. To address this, we develop an Information Feedback Evolutionary Algorithm (IFEA) that leverages feedback driven guidance to enhance the diversity and convergence of the Pareto front (PF). Simulation results show that IFEA achieves better trade offs than the other four multi-objective algorithms.
Fields of Study & Subjects
IoT and Edge/Fog Computing
UAV Applications and Optimization
Advanced Technologies in Various Fields
Publication details
- Journal / source
- IEEE Internet of Things Journal
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 13
- Issue
- 6
- Pages
- 10613–10616
- Publication date
- 12 January 2026