Passenger railway operations are based on an extensive planning process for generating the timetable, the rolling stock circulation, and the crew duties for train drivers and conductors. In particular, crew scheduling is a complex process.After the planning process has been completed, the plans are carried out in the real-time operations. Preferably, the plans are carried out as scheduled. However, in case of delays of trains or large disruptions of the railway system, the timetable, the rolling stock circulation and the crew duties may not be feasible anymore and must be rescheduled.This paper presents a method based on multi-agent techniques to solve the train driver rescheduling problem in case of a large disruption. It assumes that the timetable and the rolling stock have been rescheduled already based on an incident scenario.In the crew rescheduling model, each train driver is represented by a driver-agent. A driver-agent whose duty has become infeasible by the disruption starts a recursive task exchange process with the other driver-agents in order to solve this infeasibility. The task exchange process is supported by a route-analyzer-agent, which determines whether a proposed task exchange is feasible, conditionally feasible, or not feasible. The task exchange process is guided by several cost parameters, and the aim is to find a feasible set of duties at minimal total cost.The train driver rescheduling method was tested on several realistic disruption instances of Netherlands Railways (NS), the main operator of passenger trains in the
Large scale open, heterogeneous, distributed environments such as the Internet, are the environments in which (intelligent) agents need to be able to function and survive. These environments need to provide distributed support, including management services, for such agent systems. In this paper a local management architecture , implemented in AgentScape, is provided together with a management-oriented life cycle model. A major feature of this model is the central role of one of the states of the life cycle model, namely the "suspended" state: the state in which an agent is manageable. A prototype implementation of the management system based on the life cycle model is described.
Mobile agents require access to computing resources on heterogeneous systems across the Internet. This demo illustrates how agents can negotiate terms and conditions of resource access with one or more mediators representing virtual organizations of autonomous hosts, before migrating to a new location. Time-limited resource contracts are the result: contracts between agents and mediators, and contracts between mediators and hosts. The negotiation protocol and language are based on the WS-Agreement Specification, and have been implemented and tested within the AgentScape framework. The demonstration shows in detail how this negotiation framework has been implemented for resource access on remote, distributed systems.
Large scale open, heterogeneous, distributed environments such as the Internet, are the environments in which (intelligent) agents need to be able to function and survive. These environments need to provide distributed support, including management services, for such agent systems. In this paper a local management architecture, implemented in AgentScape, is provided together with a management-oriented life cycle model. A major feature of this model is the central role of one of the states of the life cycle model, namely the "suspended" state: the state in which an agent is manageable. A prototype implementation of the management system based on the life cycle model is described.
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