US 12,340,337 B2
Route planning for material shipping
Ghanshyam Devnani, Bengaluru (IN); Loganantha Naidu Esparan, Petaling Jaya (MY); Kumud Ranjan Jha, Bedok (SG); Vivek Luthra, Melbourne (AU); Monto Paul Rodrigues, Mumbai (IN); Sandra Orozco Martín, Barcelona (ES); Aikansh Jain, Delhi (IN); Roman Buil Giné, Barcelona (ES); Henrique Vázquez Muiños, Barcelona (ES); Quim Arnau, Barcelona (ES); Marc Blanchart Forne, Barcelona (ES); Diinalan Gunasagaram, Subang Jaya (MY); and Rodrigo Baranda Castrillo, Madrid (ES)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Feb. 24, 2023, as Appl. No. 18/113,783.
Claims priority of provisional application 63/313,817, filed on Feb. 25, 2022.
Prior Publication US 2023/0274217 A1, Aug. 31, 2023
Int. Cl. G06Q 10/083 (2024.01); G01W 1/02 (2006.01); G06N 3/126 (2023.01); G06Q 10/04 (2023.01); G06Q 10/0631 (2023.01)
CPC G06Q 10/083 (2013.01) [G01W 1/02 (2013.01); G06N 3/126 (2013.01); G06Q 10/04 (2013.01); G06Q 10/06315 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method executed by one or more processors and comprising:
receiving, by at least one processor, demand data representing types of material and quantities of the material demanded for each of a plurality of locations within a geographical area;
receiving, by the at least one processor, vessel data representing availabilities and capacities of each of a plurality of vessels;
processing, by the at least one processor, the demand data and the vessel data through a capacity optimization model to provide a first output comprising initial voyage plans for the plurality of vessels;
receiving, by the at least one processor, weather data representing predicted weather conditions within the geographical area;
processing, by the at least one processor, the first output and the weather data through a sequence optimization model to provide a second output,
wherein the second output comprising updated voyage plans for the plurality of vessels,
wherein each of the initial voyage plans and each of the updated voyage plans defines a type of the material, a quantity of the material, a vessel of the plurality of vessels, and a sequence of locations in the plurality of locations,
wherein processing the first output and the weather data through the sequence optimization model comprises executing a genetic algorithm for optimizing the initial voyage plans, and
wherein executing the genetic algorithm for optimizing the initial voyage plans comprises:
generating vector representations of variables including the sequence of locations, a speed of travel between locations of the sequence of locations, a waiting time at each of the sequence of locations for each of the plurality of vessels;
performing multiple custom mutations of the variables in each generation of a plurality of generations associated with the genetic algorithm;
iteratively optimizing the variables for each of the plurality of vessels, based on the multiple custom mutations; and
outputting an optimal solution based on the iterative optimization of the variables, wherein the optimal solution comprises a change in an engine speed of at least one vessel of the plurality of vessels moving between two locations of the sequence of locations, based on a duration of the waiting time at least one location of the sequence of locations; and
based on the updated voyage plans, transmitting, to computing systems of the plurality of vessels, instructions that cause the computing systems to adjust one or more settings of respective maneuvering systems of the plurality of vessels to voyage under the updated voyage plans, wherein the adjusted one or more settings comprises the change in the engine speed of the at least one vessel.