Distributed Matching-by-Clone Hungarian-Based Algorithm for

版本 1.0.0 (1.3 MB) 作者: Arezoo Samiei
Decentralized multi-task allocation algorithm for Multi-agent Sys with proven efficiency and conflict-free performance.
0.0
(0)
1.0 次下载
更新时间 2025/6/10

查看许可证

This repository provides the official MATLAB implementation of the Distributed Matching-by-Clone Hungarian-Based Algorithm (DMCHBA) — a novel decentralized task allocation strategy designed for multi-agent systems operating in environments with limited communication and a high number of tasks relative to agents. This algorithm was published in the IEEE Transactions on Robotics and selected for oral presentation at the 2024 IEEE International Conference on Robotics and Automation (ICRA) in Japan.
The DMCHBA framework addresses one of the most challenging scenarios in robotics: assigning multiple independent tasks to a smaller number of agents, in a way that ensures conflict-free, efficient, and scalable coordination. Unlike conventional centralized algorithms or distributed approaches with heavy communication overheads, DMCHBA leverages agent cloning, pseudo tasks, and the Hungarian method in a fully distributed and asynchronous communication setting.
DMCHBA is particularly powerful for environments where:
  • Agents cannot access global task information from a central node,
  • Communication is limited to neighbors in a dynamic or static network,
  • Optimal or near-optimal task allocation is required at scale.
This MATLAB release includes full source code, simulation data, performance plots, and two custom task sequencing strategies — the Heuristic Local Path Planning Algorithm (HLPPA) and Naive Local Path Planning Algorithm (NLPPA) — developed to enhance the order in which agents execute their assigned tasks.
🔑 Key Features:
  • Distributed coordination: Compatible with dynamic or static network topologies using local-only communication
  • Cloning-based assignment: Generates square cost matrices by replicating agents virtually (cloning), avoiding recursive Hungarian calls
  • Task flexibility: Supports any number of tasks, even when not evenly divisible by the number of agents
  • Path planning: Optional local TSP-based planning via HLPPA or NLPPA
  • Monte Carlosimulation validation: Outperforms CBBA, CBHA, and DRHBA in both total cost and execution time across 1000 Monte Carlo simulations
📁 What's Included:
  • Core implementation of the DMCHBA algorithm (dmchba.m, main.m)
  • Utility functions for task-agent cost generation and result visualization
  • Local path planning methods (HLPPA and NLPPA)
  • Input data (.mat files) for simulation runs
  • Performance comparison plots and sample result figures
  • Complete README, License (MIT), and citation details
📄 Citation:
If you use this code in your research or publications, please cite:
A. Samiei and L. Sun,
“Distributed Matching-by-Clone Hungarian-Based Algorithm for Task Allocation of Multi-Agent Systems,”
IEEE Transactions on Robotics, 2023.
https://doi.org/10.1109/TRO.2023.3335656
This research and implementation were developed by Dr. Arezoo Samiei as part of her Ph.D. dissertation and ongoing academic contributions to decentralized robotics and autonomous systems undere the supervision of Dr. Liang Sun.
👤 Author:
Arezoo Samiei, Ph.D.
Phone: +1 (575) 915-0052
Email: arsamiei@gmail.com | arezoo@nmsu.edu
LinkedIn: https://www.linkedin.com/in/arezoo-samiei
Google Scholar:
https://scholar.google.com/citations?user=XXXX (← replace XXXX with your real Scholar ID)
ORCID:
https://orcid.org/0000-0001-5812-5701

引用格式

Arezoo Samiei (2025). Distributed Matching-by-Clone Hungarian-Based Algorithm for (https://ww2.mathworks.cn/matlabcentral/fileexchange/181244-distributed-matching-by-clone-hungarian-based-algorithm-for), MATLAB Central File Exchange. 检索时间: .

MATLAB 版本兼容性
创建方式 R2023a
兼容任何版本
平台兼容性
Windows macOS Linux
标签 添加标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Arezoo-Samiei_DMCHBA_Code_NU5_NT10

版本 已发布 发行说明
1.0.0