DCA for solving the scheduling of lifting vehicle in an automated port container terminal

The container was introduced as a universal carrier for various goods in the 1960s and soon became a standard worldwide transportation. The competitiveness of a container seaport is marked by different success factors, particularly the time in port for ships. Operational problems of container termin...

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Veröffentlicht in:Computational management science Jg. 9; H. 2; S. 273 - 286
Hauptverfasser: Le, Hoai Minh, Yassine, Adnan, Moussi, Riadh
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer-Verlag 01.05.2012
Springer Nature B.V
Springer Verlag
Schlagworte:
Algorithms
Automation
Branch & bound algorithms
Business and Management
Containerization
Containers
Cranes
Cranes & hoists
Hoisting
Integer programming
Mathematical analysis
Mathematical models
Mathematics
Mixed integer
Operations Research/Decision Theory
Optimization
Optimization and Control
Original Paper
Ports
Scheduling
Studies
Success factors
Transportation terminals
Trucks
Vehicles
DCA
Automated lifting vehicle
Branch and Bound
90C26
Programmation DC
90C27
90B06
Container port terminal
ISSN:1619-697X, 1619-6988
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Beschreibung
Zusammenfassung:The container was introduced as a universal carrier for various goods in the 1960s and soon became a standard worldwide transportation. The competitiveness of a container seaport is marked by different success factors, particularly the time in port for ships. Operational problems of container terminals is divided into several problems, such as assignment of vessels, loading/unloading and storage of the containers, quay cranes scheduling cite, planning yard cranes cite and assignment of storage containers cite. In this work, the study will focus on piloting yard trucks. Two different types of vehicles can be used, namely automated guided vehicles (AGVs) and lifting vehicles (LVs). An AGV receives a container from a quay crane and transports containers over fixed path. LVs are capable of lifting a container from the ground by itself. The model that we consider is formulated as a mixed integer programming problem, and the difficulty arises when the number of binary variables increases. There are a lot of algorithms designed for mixed integer programming problem such as Branch and Bound method, cutting plane algorithm, . . . By using an exact penalty technique we treat this problem as a DC program in the context of continuous optimization. Further, we combine the DCA with the classical Branch and Bound method for finding global solutions.
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ISSN:1619-697X
1619-6988
DOI:10.1007/s10287-012-0140-8