Evrim Ursavas GüldoganÖnder BulutM. Fatih Tasgetiren2025-10-0620119789819698936, 9789819698042, 9789819698110, 9789819698905, 9789819512324, 9783032026019, 9783032008909, 9783031915802, 9789819698141, 978303198413616113349, 0302974310.1007/978-3-642-25944-9_10https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855707693&doi=10.1007%2F978-3-642-25944-9_10&partnerID=40&md5=77148d7e45a2f1bf531c208d8b37033ehttps://gcris.yasar.edu.tr/handle/123456789/10212Stochastic nature of vessel arrivals and handling times adds to the complexity of the well-known NP-hard berth allocation problem. To aid real decision-making under customer differentiations a dynamic stochastic model designed to reflect different levels of vessel priorities is put forward. For exponential interarrival and handling times a recursive procedure to calculate the objective function value is proposed. To reveal the characteristics of the model numerical experiments based on heuristic approaches are conducted. Solution procedures based on artificial bee colony and genetic algorithms covering both global and local search features are launched to improve the solution quality. The practical inferences led by these approaches are shown to be helpful for container terminals faced with multifaceted priority considerations. © 2012 Springer-Verlag. © 2012 Elsevier B.V. All rights reserved.EnglishArtificial Bee Colony, Berth Allocation, Genetic Algorithm, Prioritization, Stochastic, Artificial Bee Colonies, Berth Allocation, Berth Allocation Problem, Container Terminal, Dynamic Berth Allocation, Heuristic Approach, Local Search, Np-hard, Numerical Experiments, Objective Function Values, Prioritization, Recursive Procedure, Solution Procedure, Solution Quality, Stochastic, Stochastic Nature, Computation Theory, Genetic Algorithms, Heuristic Methods, Intelligent Computing, Recursive Functions, Stochastic Systems, Transfer Cases (vehicles), Stochastic ModelsArtificial bee colonies, Berth allocation, Berth allocation problem, Container terminal, Dynamic berth allocation, Heuristic approach, Local search, NP-hard, Numerical experiments, Objective function values, Prioritization, Recursive procedure, Solution procedure, Solution quality, stochastic, Stochastic nature, Computation theory, Genetic algorithms, Heuristic methods, Intelligent computing, Recursive functions, Stochastic systems, Transfer cases (vehicles), Stochastic modelsConference Object