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- Title
Mining rules of decision-making for fleet composition under market uncertainty using a genetic algorithm.
- Authors
Hiekata, Kazuo; Wanaka, Shinnosuke; Okubo, Yoshinori
- Abstract
This study proposes a method for determining decision-making rules on fleet composition that are effective from a perspective of profitability in the shipping industry, where there are several market uncertainties such as fuel prices, freight rates, exchange rate, transportation demand, world transportation capacity, and ship price. A simulator is used to calculate the revenue of the fleet composition based on the market scenario. Using this to optimize the buying and selling behavior of ships, decision-making rules regarding fleet composition can be determined. The rules are expressed as a vector, and a genetic algorithm (GA) is used for optimization. As a case study, the method was applied to container ships operating between Asia and Europe. The simulation revealed optimal decision-making rules. Moreover, a controlled experiment was conducted to validate the effectiveness of the rules. Participants were randomly divided into two groups: those with rules and those without rules, and they were asked to perform buying and selling behavior in a simulated environment. By comparing these groups' profits, it is validated that the rules discovered by the method are useful because they encourage decision-making from a long-term perspective.
- Subjects
ASIA; GENETIC algorithms; FREIGHT &; freightage rates; MARITIME shipping; DECISION making; CONTAINER ships; FOREIGN exchange rates; MINES &; mineral resources
- Publication
Journal of Marine Science & Technology, 2022, Vol 27, Issue 1, p730
- ISSN
0948-4280
- Publication type
Article
- DOI
10.1007/s00773-021-00864-4