{"refrec":{"BRefID":285743,"RR":"<b>Gargari, M.M.; Niasar, M.S.F.</b> (2015). A dynamic discrete berth allocation problem for container terminals, <b><i>in</i></b>: Ehlers, S. <i>et al.</i> (Ed.) <i>Maritime-port technology and development.</i> pp. 11-18","BEntID":277768,"PublicFlag":1,"CheckedFlag":1,"wosflag":0,"vabbflag":0,"RefStringPartII":", <b><i>in</i></b>: Ehlers, S. <i>et al.</i> <i>Maritime-port technology and development.</i> pp. 11-18","DocTypID":17,"DocType":"Book chapters","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Gargari, M.M.; Niasar, M.S.F.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Gargari, M.M.; Niasar, M.S.F.","Englishabstract":"In recent years, improving the process of loading and unloading ships has been the subject of much attention from the terminals operators. The importance of this issue encouraged engineers to design the best simulation for a particular model to reduce time and, subsequently, the costs of the process. The study investigates the Dynamic Berth Allocation Problem (DBAP), in which vessels are assigned to discrete positions based on their length in order to minimize vessels waiting time and berth idle time. We analysed the model by employing two highly effective meta-heuristics in the form of Local Search and Population based methods to obtain optimal solutions subject to the Variable Neighbourhood Search concept (VNS) and Genetic Algorithm (GA), respectively, and compared to each other. The results obtained through an extensive numerical analysis showed that the GA performs better than VNS to this kind of problem. 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