Dynamic vessel-to-vessel routing using level-wise evolutionary optimization

Yash Vesikar, Julian Blank, Kalyanmoy Deb, Markku Kallio, Alaleh Maskooki

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu


Modern practical optimization problems are too often complex, nonlinear, large-dimensional, and sometimes dynamic making gradient-based and convex optimization methods too inefficient. Moreover, most such problems which must be solved for a reasonably approximate solution routinely in every few hours or every day must use a computationally fast algorithm. In this paper, we present a formulation of a dynamic vessel-to-vessel service ship scheduling problem. In a span of several hours, the service ship must visit as many moving vessels as possible and complete the trip in as small a travel time as possible. Thus, the problem is bi-objective in nature and involves a time-dependent traveling salesman problem. We develop a level-wise customized evolutionary algorithm to find multiple trade-off solutions in a generative manner. Compared to a mixed-integer programming (MIP) algorithm, we demonstrate that our customized evolutionary algorithm achieves similar quality schedules in a fraction of the time required by the MIP solver. We are currently developing an interactive decision support tool based on our proposed method for finding multiple trade-off schedules simultaneously and selecting a single preferred one.

OtsikkoGECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
ISBN (elektroninen)978-1-4503-7127-8
DOI - pysyväislinkit
TilaJulkaistu - 8 heinäk. 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaGenetic and Evolutionary Computation Conference - Cancun, Meksiko
Kesto: 8 heinäk. 202012 heinäk. 2020


NimiGECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion


ConferenceGenetic and Evolutionary Computation Conference


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