Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

Angelo Alessandri (), Cristiano Cervellera, Marta Cuneo, Mauro Gaggero () and Giuseppe Soncin
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Angelo Alessandri: Department of Production Engineering, Thermoenergetics, and Mathematical Models (DIPTEM), University of Genoa, P.le Kennedy Pad. D, 16129 Genoa, Italy.
Cristiano Cervellera: Institute of Intelligent Systems for Automation (ISSIA-CNR), National Research Council of Italy, Via De Marini 6, 16149 Genoa, Italy. E-mail: cervellera@ge.issia.cnr.it; marta@ge.issia.cnr.it; gson@ge.issia.cnr.it
Marta Cuneo: Institute of Intelligent Systems for Automation (ISSIA-CNR), National Research Council of Italy, Via De Marini 6, 16149 Genoa, Italy. E-mail:marta@ge.issia.cnr.it
Mauro Gaggero: Department of Production Engineering, Thermoenergetics, and Mathematical Models (DIPTEM), University of Genoa, P.le Kennedy Pad. D, 16129 Genoa, Italy.
Giuseppe Soncin: Institute of Intelligent Systems for Automation (ISSIA-CNR), National Research Council of Italy, Via De Marini 6, 16149 Genoa, Italy. E-mails: gson@ge.issia.cnr.it

Maritime Economics & Logistics, 2009, vol. 11, issue 1, 58-76

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

Date: 2009
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