A crew task allocation and sequencing method considering workload distribution and minimum task completion time

IF 2.5 4区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS
Kybernetes Pub Date : 2024-06-03 DOI:10.1108/k-01-2024-0096
Jianhua Sun, Suihuai Yu, Jianjie Chu, Wenzhe Cun, Hanyu Wang, Chen Chen, Feilong Li, Yuexin Huang
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引用次数: 0

Abstract

Purpose

In situations where the crew is reduced, the optimization of crew task allocation and sequencing (CTAS) can significantly enhance the operational efficiency of the man-machine system by rationally distributing workload and minimizing task completion time. Existing related studies exhibit a limited consideration of workload distribution and involve the violation of precedence constraints in the solution process. This study proposes a CTAS method to address these issues.

Design/methodology/approach

The method defines visual, auditory, cognitive and psychomotor (VACP) load balancing objectives and integrates them with workload balancing and minimum task completion time to ensure equitable workload distribution and task execution efficiency, and then a multi-objective optimization model for CTAS is constructed. Subsequently, it designs a population initialization strategy and a repair mechanism to maintain sequence feasibility, and utilizes them to improve the non-dominated sorting genetic algorithm III (NSGA-III) for solving the CTAS model.

Findings

The CTAS method is validated through a numerical example involving a mission with a specific type of armored vehicle. The results demonstrate that the method achieves equitable workload distribution by integrating VACP load balancing and workload balancing. Moreover, the improved NSGA-III maintains sequence feasibility and thus reduces computation time.

Originality/value

The study can achieve equitable workload distribution and enhance the search efficiency of the optimal CTAS scheme. It provides a novel perspective for task planners in objective determination and solution methodologies for CTAS.

考虑工作量分配和最短任务完成时间的机组任务分配和排序方法
目的 在机组人员减少的情况下,优化机组任务分配和排序(CTAS)可以合理分配工作量,最大限度地缩短任务完成时间,从而显著提高人机系统的运行效率。现有的相关研究对工作量分配的考虑有限,并且在求解过程中涉及违反优先级约束。本研究针对这些问题提出了一种 CTAS 方法。该方法定义了视觉、听觉、认知和精神运动(VACP)负载均衡目标,并将其与工作负载均衡和最小任务完成时间相结合,以确保公平的工作负载分配和任务执行效率,然后构建了 CTAS 的多目标优化模型。随后,设计了保持序列可行性的种群初始化策略和修复机制,并利用它们改进了用于求解 CTAS 模型的非支配排序遗传算法 III(NSGA-III)。结果表明,该方法通过整合 VACP 负载均衡和工作量均衡,实现了公平的工作量分配。此外,改进后的 NSGA-III 保持了序列可行性,从而减少了计算时间。它为任务规划人员确定 CTAS 的目标和求解方法提供了一个新的视角。
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来源期刊
Kybernetes
Kybernetes 工程技术-计算机:控制论
CiteScore
4.90
自引率
16.00%
发文量
237
审稿时长
4.3 months
期刊介绍: Kybernetes is the official journal of the UNESCO recognized World Organisation of Systems and Cybernetics (WOSC), and The Cybernetics Society. The journal is an important forum for the exchange of knowledge and information among all those who are interested in cybernetics and systems thinking. It is devoted to improvement in the understanding of human, social, organizational, technological and sustainable aspects of society and their interdependencies. It encourages consideration of a range of theories, methodologies and approaches, and their transdisciplinary links. The spirit of the journal comes from Norbert Wiener''s understanding of cybernetics as "The Human Use of Human Beings." Hence, Kybernetes strives for examination and analysis, based on a systemic frame of reference, of burning issues of ecosystems, society, organizations, businesses and human behavior.
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