Agent-based simulation system for optimising resource allocation in production process

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Jingjing Zhao, Fan Zhang
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引用次数: 0

Abstract

Efficient sequencing of processes and resource allocation are critical in production planning scenarios, such as manufacturing workshops and construction projects, to enhance efficiency and reduce operational costs. Resource allocation in such environments is often challenged by temporal constraints, process interdependencies, and resource limitations, which complicate scheduling and increase the risk of delays. This study presents a multi-agent-based simulation system to address these challenges. A scheduling optimisation model is developed to simulate and optimise resource allocation in complex processes with network structures and temporal constraints. The primary objective is to minimise production completion time while ensuring effective resource allocation. Additionally, an adaptive, partially distributed Agent-Based Modelling and Simulation framework is proposed to simulate the execution logic of real-world processes, integrating key factors such as resource limitations, process interdependencies, and real-time decision-making. A priority-based genetic algorithm is also designed and embedded into the multi-agent system to further optimise process sequencing and resource distribution. Simulation experiments across varying case scales validate the model and algorithm. This study highlights the potential of agent-based simulation for solving complex engineering challenges and provides new insights for addressing resource allocation problems in network-structured, time-constrained environments.

Abstract Image

基于agent的生产过程资源优化配置仿真系统
高效的流程排序和资源分配对于生产计划场景(如制造车间和建筑项目)至关重要,可以提高效率并降低运营成本。在这样的环境中,资源分配经常受到时间约束、过程相互依赖和资源限制的挑战,这会使调度复杂化并增加延迟的风险。本研究提出了一个基于多智能体的仿真系统来解决这些挑战。针对具有网络结构和时间约束的复杂过程,建立了调度优化模型来模拟和优化资源分配。主要目标是在确保有效资源分配的同时最小化生产完成时间。此外,提出了一个自适应的、部分分布式的基于agent的建模与仿真框架来模拟现实世界过程的执行逻辑,该框架集成了资源限制、过程相互依赖和实时决策等关键因素。设计了一种基于优先级的遗传算法,并将其嵌入到多智能体系统中,进一步优化工艺排序和资源分配。不同情况下的仿真实验验证了模型和算法。这项研究强调了基于智能体的仿真在解决复杂工程挑战方面的潜力,并为解决网络结构、时间限制环境中的资源分配问题提供了新的见解。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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