We present a Variable Neighborhood Search heuristic for the rolling stock rescheduling problem. Rolling is needed when disruption leads to cancellations in timetable. In rescheduling, one must then assign duties, i.e., sequences of trips, available train units such way that both passenger comfort and operational performance are taken into account. For our heuristic, we introduce three neighborh...

Demand for rail travel has grown strongly within the last few years and growth is projected to continue in coming years. While central parts of the European rail network are operated punctually at its capacity limits, building new tracks is very cost intensive and thus only possible in exceptional cases. Adding new services to satisfy increasing demand is often achieved by reducing buffer times...

Jini is able to support applications in heterogeneous, dynamic computing environments and is also being used to develop agent-based applications. This paper presents the design of a multiagent framework for resource brokering and management in a Grid environment and implementation of a part of it utilizing Jini features. The multiagent framework provides services like resource brokering and all...

The current state of the art in production planning is still dominated by largely centralized solutions. More distributed approaches require a substantial increase in communication, and network load becomes an important factor. This paper presents a distributed plant automation approach based on mobile software agents and investigates the network load generated by the agents in terms of communi...

Dynamic rescheduling decision-making problem is an important issue in modern manufacturing system with the feature of combinational computation complexity. This paper introduces a multi-agent based approach using the detailed process, provided by Prometheus methodology, which used for the design of a simultaneous dynamic rescheduling decision making for flexible flow line manufacturing system t...

Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for companies. Rescheduling models are fundamental to robustness of production processes. This paper proposes model address caused by events, aiming achieve zero-defect (ZDM) concept...

In industrial resource allocation problems, an initial planning stage may solve a nominal problem instance and subsequent recovery intervene to repair inefficiencies infeasibilities due uncertainty, e.g. machine failures job processing time variations. this context, we investigate the minimum makespan scheduling problem, a.k.a. P||Cmax, under uncertainty. We propose two-stage robust approach wh...

Predictive scheduling methodologies are aimed at addressing the generation of production agendas, while assuming that all activities and resources are given and there is no uncertainty in their behavior. However, experience demonstrates that there are intrinsically uncertain parameters and that industrial environments frequently face unexpected events that force schedulers to update agendas ove...