The paper “Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints,” authored by Xueyan Sun, Weiming Shen, Jiaxin ...

Distributed Constraint Optimisation and Search Algorithms form a vital framework for addressing complex decision‐making and scheduling problems in multi-agent systems.

About A Java-based implementation of key distributed scheduling algorithms—Alt-Optimal, Odd-Even, and Sasaki. This project simulates process coordination in distributed systems and includes complexity ...

Additionally, improvements in iterated greedy algorithms have demonstrated enhanced solution quality for distributed permutation flowshop scheduling problems, effectively balancing the trade-off ...

Resource Utilization The GA-based schedule also resulted in higher resource utilization: GA: 83.9% CPU, 80.8% Memory First-Fit: 71.4% CPU, 67.1% Memory These results show that the genetic algorithm ...

We propose distributed scheduling algorithms that guarantee a constant fraction of the maximum throughput for typical wireless topologies, and have O(1) delay and complexity in the network size. Our ...

Optical communication is attracting more and more attention because of its huge bandwidth to meet the ever increasing demand of emerging computing/networking applications. In this paper we study ...