DeepACO: Neural-enhanced ant systems for combinatorial optimization
Abstract Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been
successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally …
successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally …
Glop: Learning global partition and local construction for solving large-scale routing problems in real-time
The recent end-to-end neural solvers have shown promise for small-scale routing problems
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
Joint beamforming optimization design and performance evaluation of RIS-aided wireless networks: A comprehensive state-of-the-art review
Reconfigurable intelligent surface (RIS) has emerged as a promising technology for
supporting sixth-generation (6G) wireless communication systems. RIS intelligently …
supporting sixth-generation (6G) wireless communication systems. RIS intelligently …
MGSFformer: A multi-granularity spatiotemporal fusion transformer for air quality prediction
Air quality spatiotemporal prediction can provide technical support for environmental
governance and sustainable city development. As a classic multi-source spatiotemporal …
governance and sustainable city development. As a classic multi-source spatiotemporal …
Joint task offloading and resource allocation in multi-UAV multi-server systems: An attention-based deep reinforcement learning approach
The multi-access edge computing (MEC) provides opportunities for unmanned aerial
vehicles (UAVs) to perform computing-intensive and delay-sensitive applications. To further …
vehicles (UAVs) to perform computing-intensive and delay-sensitive applications. To further …