Routing through dynamic ocean currents: General heuristics and empirical results in the Gulf Stream region

Routing through dynamic ocean currents: General heuristics and empirical results in the Gulf Stream region

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Article ID: iaor19951808
Country: United States
Volume: 29B
Issue: 2
Start Page Number: 109
End Page Number: 124
Publication Date: Apr 1995
Journal: Transportation Research. Part B: Methodological
Authors: ,
Keywords: programming: dynamic, vehicle routing & scheduling
Abstract:

Anticipating the availability of good quality ocean current data in the near future, the authors formulate the problem of routing an ocean vessel through currents to minimize fuel consumption, propose methods to increase the efficiency of the solution techniques, and simulate voyages to investigate the performance of the present approach. They formulate the problem as a dynamic program (DP) with two variables: Heading and Power (H&P). The authors then develop two heuristics, Heading-then-Power (H/P) and Heading-Alone (HA), that reduce the complexity of the formulation by decomposing the heading optimization from the power-setting optimization. To improve computational efficiency, they propose three approaches based on ship and ocean current dynamics to limit the spatial and temporal ranges that must be investigated to solve the present DP formulations. In the simulation study, these approaches reduced the spatial ranges by over one third and the temporal ranges by over 70%. The study simulated minimum fuel current routing of 96 voyages in the Gulf Stream region, leading to average fuel savings of 7.4% and 4.5% for eastbound and westbound voyages, respectively. Moreover, the simplest HA heuristic, which emphasizes heading over power optimization, provided solutions as good as those provided by the most complete H&P formulation while reducing the computational time by a factor of 40. This indicates that the shipping industry’s practice of emphasizing heading considerations seems appropriate in the current routing case and that current routing implementations and algorithmic developments might be able to reduce problem complexity by concentrating on spatial variables at the expense of temporal variables.

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