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Created with Raphaël 2.2.023Dec863230Nov299543129Oct2811916Julcleanup dec 23mastermasterwhen departure constraint is being relaxedMerge branch 'master' of https://gitlab.rrz.uni-hamburg.de/BAT9096/atfm-optimizationget feasible solution from any array, functions for solving the relaxscip, vardata updated, probdata updated, new way of finding dualmultipliercreated a function for vardata and feasible function finder. updated probdata creator function, so it can work not only for relaxscip but scip also.Delete problem_t_pricer_0_2.lpmake a feasible solution out of the relaxed solutioncomparsion between lr=1 and lr=103learning rate=1, 18990 iterationsplaying with the stepsize for faster convergenceoutput while solving the problem with stepsize = 1. @jb, I need your assistance hereadded some properties to the feasible solutoinstarting to meddle with the scip setup to integrate the solution systemright feasible solutionfirst solutionfirst feasible solutionmore on feasible solutionfinding a feasible solutionstepsize better madestepsize working wellafter presentationevaluation/presentationto execjupyter file updateddata addedafter an updateupdatedecrease significaantly the time and storage requiredDelete problem_t_pricer_12_2.lpDelete problem_t_pricer_0_2.lpcleaning up codectagssimple code for observing the solutionadditionalcontains analyzing tools for the outputcontain simple data. For restriction from the DLR, some data's were removed from this gitpython file for analyzing the output from the relax_lagr.cppMain compilor for windowsMain makefile in Linux systemslibrary for vardata_lagr.cpp