A Fully Fuzzy Linear Programming Model for Berth Allocation and Quay Crane Assignment

Gutierrez, Flabio; Lujan, Edwar; Asmat, Rafael; Vergara, Edmundo

doi:10.1007/978-3-030-03928-8_25

Cited by 3 publications

(1 citation statement)

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“…The paper [17] develops a model of fully fuzzy linear programming (FFLP) for the continuous and dynamic BAQCAP which are solved in a separate way. The arrival time of vessels is assumed to be imprecise, so that vessels can be late or early as much as a threshold allows.…”

Section: Related Workmentioning

confidence: 99%

A robust multiobjective model for the integrated berth and quay crane scheduling problem at seaside container terminals

Nourmohammadzadeh

Voß

2021

Ann Math Artif Intell

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The ever increasing demand for container transportation has led to the congestion of maritime container terminals in the world. In this work, the two interrelated problems of berth and quay crane scheduling are considered in an integrated multiobjective mathematical model. A special character of this model is that the arrival times of vessels and the failure (working) times of quay cranes are not deterministic and can vary based on some scenarios. Hence, a robust model is devised for the problem having three objectives of minimising the deviations from target berthing locations and times as well as departure delays of all vessels. This robust optimisation seeks to minimise the value of the objectives regarding all the scenarios. An exact solution approach based on the 𝜖-constraint method by the Gurobi software is applied. Moreover, regarding the complexity of the problem, two Simulated Annealing (SA) based metaheuristics, namely a Multi-Objective Simulated Annealing (MOSA) and a Pareto Simulated Annealing (PSA) approach are adapted with a novel solution encoding scheme. The three methods are compared based on some multiobjective metrics and a statistical test. The advantage of the integration of berth and quay crane scheduling is examined as well.

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Section: Related Workmentioning

confidence: 99%