DOTcvpSB: a Matlab Toolbox for Dynamic Optimization in Systems ...

DOTcvpSB: a Matlab Toolbox for Dynamic Optimization in Systems Biologydata.options.profiler test the performance of the toolbox string [’on’|’off’] ’off’data.options.multistart set 1 if the multistart is off, otherwiseinteger [positive] – 1you have to put here some in-teger valuedata.options.action what will be done string [’single-optimization’ ’single-optimization’|’re-optimization’|’hybrid-strategy’|’simulation’]11.2 DEFAULT SETTINGS OF THE SUCESSIVE RE-OPTIMIZATIONDOTcvp: dotcvp_reoptimization_default.m.m1 function [data] = dotcvp_reoptimization_default(data)23 data.option.reoptimization.NRO = 4; % compute the number of refining optimizations4 data.option.reoptimization.Increasing = 2; % how quickly will the mesh refinement be increased5 data.option.reoptimization.NLPtol = 1e-003; % initial NLP tolerance level6 data.option.reoptimization.IVPRelTol = 1e-005; % initial IVP relative tolerance level7 data.option.reoptimization.IVPAbsTol = 1e-005; % initial IVP absolute tolerance level8 data.option.reoptimization.SensAbsTol = 1e-005; % initial absolute tolerance for sensitivity variables910 % Note that values of NLP and IVP tolerances will be increased with the11 % mesh refinement algorithm until they reach the final tolerances defined12 % by the user in the initial file.1314 end11.3 DEFAULT SETTINGS OF THE HYBRID STRATEGYDOTcvp: dotcvp_hybrid_strategy_default.m.m1 function [data] = dotcvp_hybrid_strategy_default(data)23 switch data.option.HybridStrategy.method4 case{'stochastic'}5 % first step [a stochastic solver]: please fill basic settings for6 % a stochastic solver, otherwise they will be taken from the user7 % input file89 data.option.HybridStrategy.IVPRelTol = 1e-005; % IVP relative tolerance level10 data.option.HybridStrategy.IVPAbsTol = 1e-005; % IVP absolute tolerance level11 data.option.HybridStrategy.NLPTol = 1e-003; % NLP tolerance level12 data.option.HybridStrategy.NLPSolver = 'DE'; % chose a solver ['FMINCON'|'IPOPT'|'SRES'|'DE'|'ACOMI'|'MISQP'|'MITS']13 data.option.HybridStrategy.NLPsettings = 'None'; % insert the file name that contains settings for NLP solver, otherwise 'None'14 data.option.HybridStrategy.MaxIter = 50; % maximum number of iterations15 data.option.HybridStrategy.MaxCPUTime = 60*10; % maximum CPU time of the optimization (60*60*0.25) = 15 minutes16 data.option.HybridStrategy.intermediate = 'off'; % ['on'|'off'|'silent'] display of the intermediate results1718 case{'deterministic'}19 % second step [a deterministic solver]: all settings for a20 % deterministic solver are taken from the user input file, but the21 % user can introduce some new or special settings, which rewrites22 % those from the input file. The name of the structure is the same23 % as the name in the user input file, e.g. data.nlp.RHO, etc.2425 end26 end11.4 DEFAULT SETTINGS OF THE SIMULATIONDOTcvp: dotcvp_simulation_default.m.m1 function [data] = dotcvp_simulation_default(data)23 data.options.simulation.IVPsolver = 'ode15s'; % ['ode45'|'ode23'|'ode23t'|'ode23tb'|'ode113'|'ode15s'|'ode23s']4 data.options.simulation.MaxStep = 1e-1; % ['positive scalar'] step size5 data.options.simulation.grid = 'yes'; % ['yes'|'no'] display of the grid in the figure(s)6 data.options.simulation.legend = 'yes'; % ['yes'|'no'] display of the legend in the figure7 data.options.simulation.semilogx = 'no'; % ['yes'|'no'] if the logarithmic (base 10) scale is used for the X-axis8 data.options.simulation.output = 'one'; % ['one'|'all'] how many state figures will be depicted910 end11.5 DEFAULT SETTINGS OF NLP OR MINLP SOLVERSThe following are the default values for the different NLP solvers. The corresponding m-files can be editedby the user in order to change these defaults if needed.11.5.1 ACOmiDOTcvp: dotcvp_acomi_default.m1 function [data] = dotcvp_acomi_default(data)23 data.options.acomi.report = 0; % create a report file containing all solution information: [1/0] = [Yes/No]4 data.options.acomi.acc = 10^(-3); % accuracy for both: object-function & constraints5 data.options.acomi.maxeval = data.nlp.MaxIter; % maximum number of function evaluationsPage – 51