Research on Equipment Maintenance Support Technology Based on Multi-agent

Abstract

The maintenance of weapons and equipment currently is mainly regular maintenance. Due to the different running time, working conditions and personnel operation level of each equipment, the uniform maintenance requirements are not scientific. At the same time, the time, place and quantity of equipment failures are lack of effective prediction methods, therefore, the current working state of equipment maintenance is usually called “fire fighting” maintenance. With the increasing number of weapons and equipment, and the increasing complexity of technology, the existing maintenance and support methods have been unable to meet the needs of continuous intact of equipment and rapid troubleshooting. Multi-agent-based equipment maintenance support technology comprehensively considers factors such as mission requirements, equipment distribution, and equipment status, and treat each maintenance resource as an agent. Then use artificial neural network (ANN), reinforcement learning and other intelligent algorithms to realize the overall planning of maintenance and support resources. It can reduce the equipment failure rate and maintenance costs and solve the problem of unreasonable resource allocation.

Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

“…The MAS system for planning logistics distribution vehicles should clarify the hierarchical structure of each component according to the previous macro-and mesoagent modeling. At the same time, each system configuration agent should decompose the current logistics distribution vehicle planning system into several entities, encapsulate these entities into agents, and then establish an agent system model [18]. Nowadays, individual agent modeling methods are mainly divided into function-based modeling methods and physics-based modeling methods.…”