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- add config variable GENETIC_OBJECTIVES - add monitoring figure for objective space
Add a monitoring plot for the determination of composite weights for the selection of a solution from the set of non-dominated solution in case of multi-objective optimisation
Modify the code for the R-method s.t. the expansion towards an arbitray number of objectives is simple. Add a monitoring plot for the function for the determination of the composite weight. The function for the determination of composite weight and the corresponding monitoring plot will need slight adjustments for n_obj>2.
Add functionality to compare different WRT runs wrt. fuel consumption and meeting the arrival-time constraint.
Change mean speed of standard deviation to original speed value at the respective waypoint. Replace config variable BOAT_SPEED_MAX by BOAT_SPEED_BOUNDARIES which provide the minimum and maximum speed values. Speed values lower than the minimum or higher than the maximum are replaced by the respective boundaries.
According to pymoo, normalisation is not necessary here.
Prevent overwriting of parents by offspring.
Convert seconds to minutes to prevent large values of time objective. Introduce minimal time difference. Adjust container for storing objective values.
Generate convergence plots for all objectives. Visualise speed for figures showing population per generation via color code of routes.
Introduce config settings 'rndm_speed' and 'rndm_waypoints' to turn on mutation methods that only mutate the speed or the waypoints, respectively. In case 'random' is activated, both mutations for speed and waypoints are initiated for every generation.
Replace modifications of parents by those on deepcopied offspring. Prevent overwriting of GENETIC_REPAIR_TYPE. Add unit test for SpeedCrossover.
Remove if clauses that rely on BOAT_SPEED config variable default value being -99. Fix missing PosixPath to str conversion in execute_routing.py
Modify Config.check_speed_determination to meet the run modes - speed optimisation, fixed waypoints - spead and waypoint optimisation - waypoint optimisation, fixed speed Add respective unit tests.
Move code for selection from set of non-dominated solutions to a separate base class called MCDM. The implementation of the R-method is captured in a subclass RMethod.
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Related Issue / Discussion:
Enable optimisation of arrival-time accuracy in combination with fuel consumption. Enable manipulation of speed.
Changes:
Further Details:
Summary:
See internal documentation.
Dependencies:
None.