Journal of Applied Science and Engineering

Published by Tamkang University Press

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Scheduling Supervisory Tasks with Uncertainty in Human Machine Collaborative Environments: Model, Algorithm, And an Application in An International Logistics Base

 2026

 Volume 33

Zongchao Wei1,2 and Juntao Li2,3

1School of International Education, Yellow River Conservancy Technical University, kaifeng 475004, China

2North China University of Water Resources and Electric Power, Zhengzhou, 450000, China

3Kaifeng JiaoJian Industrial Investment Co., Ltd., Kaifeng 475004, China

Received: March 6, 2026
Accepted: April 29, 2026
Publication Date: July 12, 2026

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Impact of Task Scale on Algorithm Efficiency

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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To address resource scheduling challenges in the human-machine collaborative environment of the Zhengzhou International Logistics Base, this study formulates the problem as a Simultaneous Resource Scheduling Problem (SRSP) using an integer linear programming model that maximizes timely task completion and proves the problem is NP-hard when the number of resource types |R| ≥ 3. To address this challenge, A priority-based heuristic scheduling framework is proposed for human-machine collaborative supervision, featuring an offline HC algorithm for periodic tasks that dynamically prioritizes using delay risk, critical-path-based deadline partitioning, and successor influence.

Keywords: Human-machine collaborative scheduling; Logistics resource optimization; NPhard problems; Heuristic algorithms; Uncertainty modeling

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