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

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CHAPTER 11Default settingsThe user can adjust the default parameters of every module that performs of the single optimization, sucessivere-optimization, hybrid strategy or simulation. This can be done directly, by editing appropriate files located in thefollowing path:DOTcvp/src_default_valuesEach NLP or MINLP solver has its own default file with the appropriate name located into the before mentionedpath. The user can modify these default files and/or save these files under different names. Each problem can becalled and solved with the different default file what makes work with the toolbox more comfortable.11.1 DEFAULT SETTINGS OF THE SINGLE OPTIMIZATIONDOTcvp: dotcvp_single_optimization_default.moption description type options default valueInitializationdata.name name of the problem string – ’no_name’data.compilercompiler for the dynamic, sensitivities,string [’None’|’FORTRAN’] ’None’andJacobianInitializationdata.odes.Def_FORTRAN option needed only for FORTRAN string – {}parameters definitiondata.odes.parameters constant parameters before ODE string [structure] – {}data.odes.Def_MATLAB option needed only for MATLAB string [structure] – {}parameters definitiondata.odes.res problem definition in ODE form string [structure] – {”}data.odes.black_box if black box model will be used string [structure] – {’None’,’FunName’}data.odes.ic vector of initial conditions real [vector] – [ ]data.odes.NUMs number of state variables (y) integer – size(data.odes.res,2)data.odes.t0 initial time real – 0.0data.odes.tf final time real – 10.0data.odes.NonlinearSolver [reference to SUNDIALS] string [’Newton’|’Functional’] ’Newton’data.odes.LinearSolver [reference to SUNDIALS] string [’Dense’|’Diag’|’Band’ ’Dense’|’GMRES’|’BiCGStab’|’TFQMR’]data.odes.LMMLinear Multistep Method [reference string [’Adams’|’BDF’] ’Adams’to SUNDIALS]data.odes.MaxNumStep maximum number of steps [referenceinteger – 500to SUNDIALS]data.odes.RelTolIVP relative tolerance level [referencereal [positive] – 1*10 ˆ (-7)to SUNDIALS]data.odes.AbsTolIVP absolute tolerance level [referencereal [positive] – 1*10 ˆ (-7)to SUNDIALS]data.sens.SensAbsTol absolute tolerance for sensitivity real [positive] – 1*10 ˆ (-7)variables [reference to SUNDIALS]data.sens.SensMethod [reference to SUNDIALS] string [’Staggered’|’Staggered1’ ’Staggered’|’Simultaneous’]data.sens.SensErrorControl sensitivities correction [reference toSUNDIALS]string [’on’|’off’] ’on’
DOTcvpSB: a Matlab Toolbox for Dynamic Optimization in Systems BiologyNLP definitiondata.nlp.RHO number of time intervals integer – 10data.nlp.problem problem definition string [’min’|’max’] ’min’data.nlp.J0 cost function (performance index) string – ”data.nlp.u0 initial value for control values real [vector] – []data.nlp.lb lower bounds for control values real [vector] – []data.nlp.ub upper bounds for control values real [vector] – []data.nlp.p0initial values for time-independent real [vector] – []parametersdata.nlp.lbplower bounds for time-independent real [vector] – []parametersdata.nlp.ubpupper bounds for time-independent real [vector] – []parametersdata.nlp.solver NLP or MINLP solver which will be string [’FMINCON’|’IPOPT’ ’FMINCON’used for the optimization|’SRES’|’DE’data.nlp.SolverSettingsinsert the name of the file that containssettings for NLP or MINLPsolver, if does not exist use [’None’]|’ACOMI’|’MISQP’|’MITS’]string – [’None’]data.nlp.NLPtol NLP tolerance level real – 1*10 ˆ (-5)data.nlp.GradMethod gradient method used for determinist string [’SensitivityEq’ ’SensitivityEq’NLP or MINLP solvers|’FiniteDifference’|’None’]data.nlp.MaxItermaximum number of function evaluationsinteger [positive] – 1000data.nlp.MaxCPUTime maximum CPU time of the optimizationreal [positive] – 60*60*0.25(60*60*0.25) = 15 minutesdata.nlp.approximation control approximation string [’PWC’|’PWL’] ’PWC’data.nlp.FreeTime set ’on’ if free time is considered string [’on’|’off’] ’off’data.nlp.t0Timeinitial size of the time intervals, real [vector positve] – [data.odes.tf/data.nlp.RHO]e.g. [data.odes.tf/data.nlp.RHO] orfor the each time interval separately[dt1 dt2 dt3]data.nlp.lbTime lower bound of the time intervals real [positive] – 0.01data.nlp.ubTime upper bound of the time intervals real [positive] – data.odes.tfdata.nlp.NUMc number of control variables (u) integer [positive] – size(data.nlp.u0,2)data.nlp.NUMi number of integer variables (u)taken from the last control variables,if not equal to 0 youneed to use some MINLP solver[’ACOMI’|’MISQP’|’MITS’]data.nlp.NUMpnumber of time-independent parameters(p)integer [0 or positive] – 0integer [0 or positive] – size(data.nlp.p0,2)Equality constraints (ECs)data.nlp.eq.status if equality constraints are presented string [’on’|’off’] ’off’data.nlp.eq.NEC number of active ECs integer [0 or positive] – 1data.nlp.eq.eq equality constraints string [structure] – {”}data.nlp.eq.timetime when equality constraints are string [structure] – data.nlp.RHOactivedata.nlp.eq.PenaltyFun ’on’ or ’off’ the penalty function string [’on’|’off’] ’off’data.nlp.eq.PenaltyCoe penalty function for equality constraintsreal – 1.0Inequality /path/ constraints (INECs)data.nlp.ineq.status if inequality constraints are presentedstring [’on’|’off’] ’off’data.nlp.ineq.NECnumber of active inequality constraintsinteger [0 or positive] – 2data.nlp.ineq.InNUM how many inequality constraints are integer [0 or positive] – 1’more’ else ’less’data.nlp.ineq.eq inequality constraints string [structure] – {”}data.nlp.ineq.PenaltyFun ’on’ or ’off’ the penalty function string [’on’|’off’] ’off’data.nlp.ineq.PenaltyCoe penalty function for the inequalityconstraintsreal [vector] – [1.0 1.0]Options for setting of the final outputdata.options.intermediate display of the intermediate results string [’on’|’off’] ’off’data.options.display display of the figures string [’on’|’off’] ’on’data.options.title display of the titles string [’on’|’off’] ’on’data.options.state display of the state trajectory string [’on’|’off’] ’on’data.options.control display of the control trajectory string [’on’|’off’] ’on’data.options.ConvergCurve display of the convergence curve string [’on’|’off’] ’on’NLP definitiondata.options.Pict_Format save figures as string [’eps’|’wmf’|’both’] ’eps’data.options.report save data in the dat file string [’on’|’off’] ’on’data.options.commands additional commands, e.g. ’figure(1),..string – {”}’data.options.trajectories how many state trajectories will bedisplayedstring – size(data.odes.res,2)Page – 50
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