This paper presents an agent-based approach to online assembly task allocation and scheduling for flexible assembly systems. We propose an anytimescheduling algorithm to handle dynamic changes during planning. This algorithm is the center of an agent-based architecture in which agents for scheduling, collision avoidance, task execution, and task monitoring collaborate to overcome unexpected exe...

This work provides an overview on current efforts for communication between interconnected electric vehicles and supply equipments also known as Vehicle-to-Grid (V2G) communication. Such efforts are core enablers for electric vehicles being used for demand side management. Hence this work investigates the ability to adapt the EV charging process in near real-time in case of grid violations thro...

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...

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...

This work introduces a MILP reactive scheduling framework for resource-constrained multistage batch facilities with multiple parallel units at each stage. The approach is based on a continuous time domain representation that takes into account the schedule currently in progress, the updated information on the old production orders still to be processed, new order arrivals, the present plant sta...

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...