{"title":"Design and Evaluation of an Integrated Autonomous Control Method for Automobile Terminals","authors":"M. Görges, M. Freitag","doi":"10.3390/logistics6040073","DOIUrl":null,"url":null,"abstract":"Background: Automobile terminals play a key role in global finished car supply chains. Due to their connecting character between manufacturers on the one side and distributers on the other side, they are continuously faced with volatile demand fluctuations and unforeseen dynamic events, which cannot be handled adequately by existing planning methods. Autonomous control concepts already showed promising results coping with such dynamics. Methods: This paper describes the causes of dynamics and the terminal systems’ inherent shortcomings in dealing with such dynamics. On this basis, it derives terminal’s demand for novel planning approaches and presents a new integrated autonomous control method for automobile terminals. This novel autonomous control approach combines yard and berth assignments. This paper evaluates the performance of the new approach in a small comprehensive generic scenario. It compares classical planning approaches with the new autonomous control approach, by using a discrete event simulation model. Moreover, it analyses all relevant parameters of the new approach in a full factorial experiment design. In a second step this paper proves the applicability of the combined autonomous control approach to real-world terminals. It presents a simulation model of a real-world terminal and compares the new method with the existing terminal planning approaches. Results: This paper will show that the autonomous control approach is capable of outperforming existing centralized planning methods. In the generic and in the real-world case the new combined method leads to the best logistic target achievement. Conclusions: The new approach is highly suitable to automobile terminal systems and helps to overcome existing shortcomings. Especially in highly dynamic and complex settings, autonomous control performs better than conventional yard planning approaches.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Logistics-Basel","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/logistics6040073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 1
Abstract
Background: Automobile terminals play a key role in global finished car supply chains. Due to their connecting character between manufacturers on the one side and distributers on the other side, they are continuously faced with volatile demand fluctuations and unforeseen dynamic events, which cannot be handled adequately by existing planning methods. Autonomous control concepts already showed promising results coping with such dynamics. Methods: This paper describes the causes of dynamics and the terminal systems’ inherent shortcomings in dealing with such dynamics. On this basis, it derives terminal’s demand for novel planning approaches and presents a new integrated autonomous control method for automobile terminals. This novel autonomous control approach combines yard and berth assignments. This paper evaluates the performance of the new approach in a small comprehensive generic scenario. It compares classical planning approaches with the new autonomous control approach, by using a discrete event simulation model. Moreover, it analyses all relevant parameters of the new approach in a full factorial experiment design. In a second step this paper proves the applicability of the combined autonomous control approach to real-world terminals. It presents a simulation model of a real-world terminal and compares the new method with the existing terminal planning approaches. Results: This paper will show that the autonomous control approach is capable of outperforming existing centralized planning methods. In the generic and in the real-world case the new combined method leads to the best logistic target achievement. Conclusions: The new approach is highly suitable to automobile terminal systems and helps to overcome existing shortcomings. Especially in highly dynamic and complex settings, autonomous control performs better than conventional yard planning approaches.