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Genetic algorithms to schedule container transfers at multimodal terminals
Author(s) -
Kozan E.,
Preston P.
Publication year - 1999
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/j.1475-3995.1999.tb00158.x
Subject(s) - container (type theory) , computer science , schedule , genetic algorithm , transfer (computing) , port (circuit theory) , throughput , yard , set (abstract data type) , mathematical optimization , sensitivity (control systems) , algorithm , implementation , parallel computing , mathematics , operating system , engineering , machine learning , mechanical engineering , physics , electrical engineering , quantum mechanics , electronic engineering , wireless , programming language
Optimising the container transfer schedule at the multimodal terminals is known to be NP‐hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near‐optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.