Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming
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Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming Angelo Alessandria,*, Cristiano Cervellerab, Mauro Gaggeroa,b and Giuseppe Soncinb
Marta
Cuneob,
a
Department of Production Engineering, Thermoenergetics, and Mathematical Models (DIPTEM), University of Genoa, P.le Kennedy Pad. D, 16129 Genoa, Italy. E-mails: [email protected], [email protected] b Institute of Intelligent Systems for Automation (ISSIA-CNR), National Research Council of Italy, Via De Marini 6, 16149 Genoa, Italy. E-mails: [email protected], [email protected], gson@ge. issia.cnr.it *Correspondence.
Abstract
The increase in efficiency of container terminals is addressed via an approach based on the optimisation of logistics operations. Toward this end, a discrete-time dynamic model of the various flows of containers that are inter-modally routed from arriving carriers to carriers ready for departure is proposed. On the basis of such a model, the decisions on the allocation of the available handling resources inside a container terminal are made according to the predictive-control approach by minimising a performance cost function over a forward horizon from the current time instant. Since both the dynamic equations and the cost function are in general nonlinear and since binary variables are used to model the departure or stay of a carrier, such decisions result from the on-line solution of a mixed-integer nonlinear programming problem at each time step. To solve this problem, two techniques are proposed that have to deal explicitly with the binary variables and with the nonlinearities of the model and the cost function. The first relies on the application of a standard branch-and-bound algorithm. The second is based on the idea of treating the decisions associated with the binary variables as step functions. Simulation results are reported to illustrate the pros and cons of such methodologies in a case study.
Maritime Economics & Logistics (2009) 11, 58–76. doi:10.1057/mel.2008.24
58
r 2009 Palgrave Macmillan 1479-2931 Maritime Economics & Logistics www.palgrave-journals.com/mel/
Vol. 11, 1, 58–76
Management of logistics operations
Keywords: container terminal; dynamic model; mixed-integer programming; nonlinear programming; predictive control
Introduction The considerable growth of container shipping makes it crucial to attain the goal of an efficient management of container terminals. This is difficult to achieve because of the complexity of the logistic operations carried out at modern terminals. Concerning such topic are various problems that have significantly attracted the attention of the research community (Steenken et al, 2004; Stahlbock and Voss, 2008). It is often necessary to devise models to evaluate the performances of a container terminal. Toward this end, standard results from queuing theory were proposed by Van Hee et al (1988) and Van Hee and Wijbrands (1988). The main drawback of such an approach is the poor capability of describi
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