ABSTRACT
As thehighly complex logistics system, container terminal logistics systems (CTLS)play an increasingly important role in modern international logistics, andtherefore their scheduling and decision-making process of much significance tothe operation and competitiveness of harbors. In this paper, the handling,stacking and transportation in CTLS are regardedas a kindof generalized computingand compared with the working in general computer systems, whereupon theHarvard architecture and agent-based computing paradigm are fused to model the operationalprocessing of CTLS, and the kernel thoughts in computer organization, architectureand operating system are introduced into CTLS to support and evaluate containerterminal planning, scheduling and decision-making. A new agile, efficient androbust compound modeling and scheduling methodology for CTLS is obtained consequently.Finally aseries of single-vessel simulations on handlingand transportationare designed, implemented, performed, evaluated and analyzed, which validatethe feasibility and creditability of the systematicmethodology effectively
1. INTRODUCTION
Since introducedin the 1960s, containers represent the standard unit load concept forinternational freight. Containerized traffic and information network bothprovide a common basis for international logistics system nowadays. Startingwith 50 million twenty-foot equivalent unit (TEU) in 1985, world containerturnover has reached more than 350 million TEU in 2004, and the annual growth rateis projected at 10 percent till 2020. Today over 60% of the world’s deep-seageneral cargo is transported by containers, whereas some routes, especiallybetween economically strong and stable countries, are containerized up to 100%(Steenken, Voss, and Stahlbock 2004). The increasing number of containershipments causes higher demands on the seaport container terminals, containerlogistics, and management, as well as technical equipments. An increasedcompetition between seaports, especially between geographically close ones, isa result of this development. At the same time, harbors have to gear up to meetthe challenge of handling mega-vessels capable of carrying 10,000–12,000 TEU and beyond (Stahlbockand Voss 2008). To win an advantage in the new round terminal competition,container terminal logistics systems (CTLS) must be systematic rationalized, efficientandrobust,and couldprovide a first-class container logistics handling platform for the loading andunloading of container ships and trucks. The only effective approach to achievethis purpose is optimizing task assignment, resources allocation and schedulingmanagement at container terminals.
Thereupon,much pertinent research has been on the marchor educed the corresponding results. For instance, Gunther and Kim(2006) summarized the container traffic, operation and the interrelated planningand scheduling problems. Vis and Koster (2003)gave a classification of the decision problems that arose at containerterminals under the background of the ships have been increasing large-scale. Henesey,Davidsson, and Persson (2006),and Kefi, Korbaa, Ghedira, and Yim (2007) appliedmulti-agent into container terminal scheduling system, which madethe scheduling system intelligentand provide the scientific proofs for the scheduling and decision-making of theproduction and management at container terminals.