Authors:
            
                    Shijie Li
                    
                        
                    
                    ; 
                
                    Rudy R. Negenborn
                    
                        
                    
                     and
                
                    Gabriel Lodewijks
                    
                        
                    
                    
                
        
        
            Affiliation:
            
                    
                        
                    
                    Delft University of Technology, Netherlands
                
        
        
        
        
        
             Keyword(s):
            Multi-agent Systems, Constraint Optimization, Planning and Scheduling.
        
        
            
                Related
                    Ontology
                    Subjects/Areas/Topics:
                
                        Agents
                    ; 
                        Artificial Intelligence
                    ; 
                        Artificial Intelligence and Decision Support Systems
                    ; 
                        Constraint Satisfaction
                    ; 
                        Distributed and Mobile Software Systems
                    ; 
                        Distributed Problem Solving
                    ; 
                        Enterprise Information Systems
                    ; 
                        Formal Methods
                    ; 
                        Industrial Applications of AI
                    ; 
                        Informatics in Control, Automation and Robotics
                    ; 
                        Intelligent Control Systems and Optimization
                    ; 
                        Knowledge Engineering and Ontology Development
                    ; 
                        Knowledge-Based Systems
                    ; 
                        Multi-Agent Systems
                    ; 
                        Planning and Scheduling
                    ; 
                        Simulation and Modeling
                    ; 
                        Soft Computing
                    ; 
                        Software Engineering
                    ; 
                        Symbolic Systems
                    
            
        
        
            
                Abstract: 
                Vessel rotation planning concerns the problem of assigning rotations to vessels over a number of terminals for
loading and unloading containers in a large port. Vessel operators and terminal operators communicate with
each other to make appointments about the rotation plans for the vessels. However, it happens frequently that
these appointments cannot be met. Thus, it is important to generate the rotation plans for the vessel operators
in an efficient automated way. In this paper, we propose an approach to solve the vessel rotation planning
problem by modeling the problem as a layered distributed constraint optimization problem (DCOP). To
evaluate the performance of the proposed approach, combinations of three DCOP algorithms are considered,
namely, Asynchrounous Forward Bounding, Synchrounous Branch and Bound, and Dynamic Programming
Optimization Protocol. We evaluate the solution quality and computational and communication costs of these
three algorithms when solving the vessel rot
                ation planning problem using the proposed layered formulation.
                (More)