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Existing approaches solving multi-vehicle pickup and delivery problems with soft time windows typically use common benchmark sets to verify their performance. However, there is a gap from these benchmark sets to real world problems with respect to instance size and problem complexity. In this paper we show that a combination of existing approaches together with improved heuristics is able to deal with the instance sizes and complexity of real world problems. The cost savings potential of the heuristics is compared to human dispatching plans generated from the data of a European carrier.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2010. While last year’s TDP focused on decisions making using extended behavior networks and on its software architecture and implementation in this year we describe the tool set that was created for RoboCup 3D. It contians a GUI for agent- and world state visualization, for evaluation of localization algorithms and benchmarks in general, a visual editor for Extended Behavior Networks creation and debugging, a live movement tool to interact with the joints and finally a tool for editing behavior motor files.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2009. It focuses on two distinctive features of the team: decisions making using extended behavior networks and its software architecture and implementation in Java to open the simulation for the Java community.