Frontiers

Enhancing multi-objective evolutionary algorithms with machine learning for scheduling problems: recent advances and survey

Multi-objective scheduling problems in workshops are commonly encountered challenges in the increasingly competitive market economy. These scheduling problems require a trade-off among multiple ...
IEEE

Heuristic Scheduling Algorithm for Workflow Applications in Cloud-Fog Computing Based on Realistic Client Port Communication

Abstract: Cloud-fog computing systems require task scheduling to efficiently manage resources and ensure timely task execution in a distributed environment. Fog computing extends computation, storage, ...
GitHub

CPU Scheduling Algorithm Simulator

An interactive simulator for learning and testing various CPU scheduling algorithms, including First Come First Serve (FCFS), Round Robin(RR), Shortest Job First(SJF) and Shortest Remaining Time First ...
IEEE

Optimized CQF Scheduling in TSN: A Formal Architecture-Based Neuro-Tabu Optimized Scheduling Algorithm

Abstract: Efficient real-time communication in Time-Sensitive Networking (TSN) relies on precise flow scheduling to meet stringent latency and reliability requirements. However, under the Cyclic ...
Frontiers

Research on a multilevel scheduling model for multi variety and variable batch production environments based on machine learning

1 Beijing University of Technology, Faculty of Materials and Manufacturing, Beijing, China 2 Capital Aerospace Machinery Co., Ltd., Beijing, China Traditional manufacturing enterprises cannot adjust ...
GitHub

Job Scheduling Problem Solver

A comprehensive solution for the Job Scheduling Problem using multiple algorithms including Backtracking and Genetic Algorithm approaches. Features both graphical and command-line interfaces for easy ...