SwarmFabSim: A Simulation Framework for Bottom-up Optimization in Flexible Job-Shop Scheduling using NetLogo

被引:4
作者
Umlauft, M. [1 ]
Schranz, M. [1 ]
Elmenreich, W. [2 ]
机构
[1] Lakeside Labs GmbH, Klagenfurt, Austria
[2] Univ Klagenfurt, Inst Networked & Embedded Syst, Klagenfurt, Austria
来源
PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON SIMULATION AND MODELING METHODOLOGIES, TECHNOLOGIES AND APPLICATIONS (SIMULTECH) | 2022年
关键词
Swarm Intelligence; Flexible Job-Shop Scheduling; Agent-based Modeling; ALGORITHM;
D O I
10.5220/0011274700003274
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper models and simulates a semiconductor production plant organized by the job-shop principle as a self-organizing system using swarm intelligence algorithms in an agent-based simulation tool. We model a set of agents, including machines, workcenters, lots and processes. To simulate our model, we use NetLogo, one of the most widely used agent-based simulation platforms. The framework for the simulation was built as a structured system of code modules using a callback architecture that allows to exchange the used swarm algorithm easily. The user can configure their own fab model and simulations via the user interface and configuration files. The resulting log files include several key performance indicators: makespan, average flow factor, and lot tardiness. We offer the framework including sample swarm algorithms running on NetLogo version 6.1 and later as open source on GitHub.
引用
收藏
页码:271 / 279
页数:9
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