Preference-based evolutionary multi-objective optimization in ship weather routing

Joanna Szłapczyńska; Rafał Szłapczyński

doi:10.1016/j.asoc.2019.105742

Preference-based evolutionary multi-objective optimization in ship weather routing

Abstrakt

In evolutionary multi-objective optimization (EMO) the aim is to find a set of Pareto-optimal solutions. Such approach may be applied to multiple real-life problems, including weather routing (WR) of ships. The route should be optimal in terms of passage time, fuel consumption and safety of crew and cargo while taking into account dynamically changing weather conditions. Additionally it must not violate any navigational constraints (neither static nor dynamic). Since the resulting non-dominated solutions might be numerous, some user support must be provided to enable the decision maker (DM) selecting a single ‘‘best’’ solution. Commonly, multi-criteria decision making methods (MCDM) are utilized to achieve this goal with DM’s preferences defined a posteriori. Another approach is to apply DM’s preferences into the very process of finding Pareto-optimal solutions, which is referred to as preference-based EMO. Here the Pareto-set is limited to those solutions, which are compliant with the pre-configured user preferences. The paper presents a new tradeoff-based EMO approach utilizing configurable weight intervals assigned to all objectives. The proposed method has been applied to ship WR problem and compared with a popular reference point method: r-dominance. Presented results prove applicability and competitiveness of the proposed method to solving multi-objective WR problem.

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Web of Science
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Autorzy (2)

Joanna Szłapczyńska dr hab. inż.
Rafał Szłapczyński dr hab. inż.

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Wersja publikacji: Accepted albo Published Version
Licencja: otwiera się w nowej karcie

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Kategoria:

Publikacja w czasopiśmie

Typ:

artykuły w czasopismach

Opublikowano w:

APPLIED SOFT COMPUTING nr 84, strony 1 - 21,
ISSN: 1568-4946

Język:

angielski

Rok wydania:

2019

Opis bibliograficzny:

Szłapczyńska J., Szłapczyński R.: Preference-based evolutionary multi-objective optimization in ship weather routing// APPLIED SOFT COMPUTING -Vol. 84, (2019), s.1-21

DOI: