A Dynamic Scheduling Multiagent System for Truck Dispatching in Open-Pit Mines

被引:4
作者
Ahumada, Gabriel Icarte [1 ,2 ]
Pinto, Jean Diaz [3 ]
Herzog, Otthein [4 ,5 ,6 ]
机构
[1] Univ Bremen, Int Grad Sch Dynam Logist IGS, Bremen, Germany
[2] Arturo Prat Univ UNAP, Fac Engn & Architecture, Iquique, Chile
[3] Arturo Prat Univ UNAP, Sci Fac, Iquique, Chile
[4] Univ Bremen, TZI Ctr Comp Technol, Bremen, Germany
[5] Jacobs Univ, Bremen, Germany
[6] Tongji Univ Shanghai, Shanghai, Peoples R China
来源
AGENTS AND ARTIFICIAL INTELLIGENCE, ICAART 2020 | 2021年 / 12613卷
关键词
Truck dispatching; Open-pit mine; Multiagent systems; Scheduling; Rescheduling;
D O I
10.1007/978-3-030-71158-0_6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Material handling is an important process in the mining industry because of its high operational cost. In this process, shovels extract and load materials that must be transported by trucks to different destinations at the mine. When a truck ends an unloading operation, it requires a new loading destination. If a centralized system provides destinations by following dispatching criteria, then one of the main disadvantages of this kind of systems is not being able to provide a precise dispatching solution without knowledge about potentially changed external conditions and the dependency on a central node. In this paper, we describe a distributed approach based on Multiagent Systems (MAS) to alleviate these disadvantages. In this approach, the real-world equipment items such as shovels and trucks are represented by intelligent agents. The agents interact with each other to generate schedules for the machines that they represent. For this interaction, a Contract Net Protocol with a confirmation stage was implemented. In addition, when a machine failure occurs, the agents are able to update their schedules. In order to evaluate the MAS, an agent-based simulation with data from a Chilean open-pit mine was used. The results show that the MAS is able to generate the schedules in a practical computation time-frame. The schedules generated by the MAS decrease the truck cost by 17% on average. Moreover, when a machine failure occurs, the agents are able to repair their schedules in a short period of time.
引用
收藏
页码:132 / 148
页数:17
相关论文
共 30 条
[1]  
Adams K.K., 2016, P 4 UMAT BIENN INT M, P60
[2]   An extended multi-agent negotiation protocol [J].
Aknine, S ;
Pinson, S ;
Shakun, MF .
AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2004, 8 (01) :5-45
[3]  
Alarie S., 2002, INT J SURFACE MINING, V16, DOI [10.1076/ijsm.16.1.59, DOI 10.1076/IJSM.16.1.59]
[4]   Development of a scenario-based robust model for the optimal truck-shovel allocation in open-pit mining [J].
Bakhtavar, E. ;
Mahmoudi, H. .
COMPUTERS & OPERATIONS RESEARCH, 2020, 115
[5]  
Bellifemine FL, 2007, DEV MULTIAGENT SYSTE, V7
[6]   Modelling and Optimizing an Open-Pit Truck Scheduling Problem [J].
Chang, Yonggang ;
Ren, Huizhi ;
Wang, Shijie .
DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2015, 2015
[7]   Digitalization of mine operations: Scenarios to benefit in real-time truck dispatching [J].
Chaowasakoo, Patarawan ;
Seppala, Heikki ;
Koivo, Heikki ;
Zhou, Quan .
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY, 2017, 27 (02) :229-236
[8]   A reactive multi-agent approach for online (re)scheduling of resources in port container terminals [J].
Chargui, Kaoutar ;
El Fallahi, Abdellah ;
Reghioui, Mohamed ;
Zouadi, Tarik .
IFAC PAPERSONLINE, 2019, 52 (13) :124-129
[9]  
Costa Felippe Pereira da, 2005, Rem: Rev. Esc. Minas, V58, P77, DOI 10.1590/S0370-44672005000100013
[10]   On agent-based decentralized and integrated scheduling for small-scale manufacturing [J].
Gehlhoff, Felix ;
Fay, Alexander .
AT-AUTOMATISIERUNGSTECHNIK, 2020, 68 (01) :15-31