Title: Parametric analysis of evolutionary algorithms for the storage location of outbound containers at a seaport terminal

Authors: José Maria A. Pangilinan; Gerrit K. Janssens; Etsuko Nishimura

Addresses: School of Computing and Information Sciences, Saint Louis University, Gen. Luna Street, Baguio City, Philippines ' Operations Management and Logistics, Hasselt University, Agoralaan 1, B-3590 Diepenbeek, Belgium ' Graduate School of Maritime Sciences, Kobe University, 5-1-1, Fukaeminami-machi, Higashinada-ku, 658-0022 Kobe, Japan

Abstract: The research aims to minimise the handling time of containers in the storage yard. In such a way it finds an efficient strategy and a loading schedule that avoids unnecessary container moves in the yard. Two loading strategies are examined, namely LCFS and FCFS in terms of handling time in the storage area. Results show that an LCFS loading schedule is far more efficient than an FCFS schedule. A genetic algorithm (GA) is used to optimise both loading schemes. The objectives of the optimisation problem are two-fold: on the one hand one wants to minimise the handling time, and on the other hand one wants to minimise the number of re-handles. The effect of the genetic operators on the solutions are analysed and results show that a GA with mutation as operator only is best in finding efficient solutions. A sensitivity analysis based on Sobol's method is carried out to test the importance of the parameter values of the GA.

Keywords: terminal operations modelling; seaport terminals; evolutionary algorithms; container storage location; parametric analysis; handling time; container handling; loading scheduling; genetic algorithms; GAs; containers.

DOI: 10.1504/IJMOM.2013.052066

International Journal of Modelling in Operations Management, 2013 Vol.3 No.1, pp.31 - 52

Published online: 29 Jan 2014 *

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