In this paper, we present a two-stage optimization model for the machinery system selection problem. The objective is to minimize total cost, while aggregated power requirement and emission regulations are constraining the problem. Future fuel prices are considered to be uncertain. From a set of alternatives, the machinery configuration providing the lowest total cost is found. Also design flexibility in terms of future reconfiguration possibilities is taken into account. The machinery selection for a 2000 TEU container vessel is used as an illustrative case. Five initial machinery concepts are considered: diesel machinery, diesel machinery with a scrubber system, dual fuel (DF) machinery, pure gas engines, and a DF ready machinery. There is also a set of reconfiguration possibilities available for each alternative. From solving the case study, DF machinery is found optimal, while pure gas machinery is close to equally good. By solving the problem with deterministic fuel prices, the value of flexibility is not properly accounted for, resulting in an unreasonably high total cost for the flexible machinery alternatives. This demonstrates the need for a decision support approach that explicitly handles future uncertainty, as the two-stage stochastic model presented in this paper does.


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    Titel :

    A two-stage optimization approach for sulphur emission regulation compliance


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2017-01-02


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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