A multi-objective berth allocation problem in fuzzy environment

The Berth Allocation Problem (BAP) is an important seaside problem in port logistics, which involves the determination of berthing times and positions of arriving vessels in a wharf. Most studies have considered that vessels arrival and handling times are known fixed quantities available to wharves...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 500; S. 341 - 350
Hauptverfasser:	Pérez-Cañedo, Boris, Verdegay, José Luis, Rosete, Alejandro, Concepción-Morales, Eduardo René
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 21.08.2022
Schlagworte:	Fully fuzzy berth allocation problem Fully fuzzy multi-objective linear programming Fuzzy epsilon-constraint method Fuzzy inequality constraint Lexicographic ranking criteria Fuzzy inequality constraint Fuzzy epsilon-constraint method Fully fuzzy berth allocation problem Fully fuzzy multi-objective linear programming Lexicographic ranking criteria
ISSN:	0925-2312, 1872-8286
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Zusammenfassung:	The Berth Allocation Problem (BAP) is an important seaside problem in port logistics, which involves the determination of berthing times and positions of arriving vessels in a wharf. Most studies have considered that vessels arrival and handling times are known fixed quantities available to wharves operators beforehand. However, due to many uncontrollable factors that can affect vessels arrival and handling times, those quantities are highly uncertain and may have a significant impact in the wharf operation. This paper takes fuzzy uncertainty into account and presents a fully fuzzy BAP with two objective functions. Specifically, it is considered the minimisation of the total waiting time of vessels and the makespan of the wharf operation. The problem is solved by using two lexicographic methods for fully fuzzy multi-objective linear programming (FFMOLP). Multiple Pareto optimal fuzzy solutions are obtained using a fuzzy epsilon-constraint method. Results demonstrate the effectiveness of the proposed approaches in handling fuzziness and conflicting objectives in a BAP. Moreover, from a methodological point of view, results show that it is best to use lexicographic ranking criteria instead of linear ranking functions for solving the associated FFMOLP problem.
ISSN:	0925-2312 1872-8286
DOI:	10.1016/j.neucom.2021.08.161