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

delete2019-11-01
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OA
AI
J
Joanna Szłapczyńska *
R
Rafał Szłapczyński
DOI:10.1016/j.asoc.2019.105742delete
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Abstract

Abstract

En 中文
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. (C) 2019 The Authors. Published by Elsevier B.V.
Keywords:
Ship weather routing
Multi-objective optimization
Decision maker's preferences
Weight intervals
Trade-off

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

F
fahrenheit universities
Scholars:
1.6W
Papers: 1.3W
Citations: 21
G
Gdynia Maritime University
Scholars:
370
Papers: 356
Citations: 377
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