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EconomicOptimization.m

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+clc
+format long
+parpool('local', 12);
+
+addpath('CycleSteps')
+addpath('GA_files')
+
+load('Params')
+
+N = 10 ;
+type = 'EconomicEvaluation' ;
+
+for i = 12:12
+
+% load parameters
+IsothermParams     = IsothermPar(i, :) ;
+material_propertry = SimParam(i, :)    ;
+
+material    = {}                 ;
+material{1} = material_propertry ;
+material{2} = IsothermParams     ;
+
+Function = @(x) PSACycleSimulation( x, material, type, N ) ; % Function to simulate the PSA cycle
+
+% initial variables
+[~, vars] = sortt(loadpopfile('UTSA-16_Process.txt'));
+vars = [vars, ones(length(vars), 1), 1e4*ones(length(vars), 1)];
+
+options            = nsgaopt();                          % create default options structure
+options.popsize    = 60;                                 % populaion size
+options.outputfile = 'UTSA-16_Economic.txt';
+options.maxGen     = 80;                                 % max generation
+
+options.vartype    = [1, 1, 1, 1, 1, 1] ;
+
+options.initfun={@Pop_Override, vars}   ;                % Supply variables from previous results
+
+options.numObj  = 2 ;                                    % number of objectives
+options.numVar  = 6 ;                                    % number of design variables
+options.numCons = 3 ;                                    % number of constraints
+options.lb = [1e5,  10, 0.01, 0.1, 0, 1e4]   ;           % lower bound of x
+options.ub = [10e5, 1000, 0.99, 2, 1, 5e4]   ;           % upper bound of x
+options.nameObj = {'-productivity','energy'} ;           % the objective names are showed in GUI window.
+options.objfun  = Function                   ;           % objective function handle
+
+options.useParallel = 'yes' ;                            % parallel computation is non-essential here
+options.poolsize     = 12   ;                            % number of worker processes
+
+result = nsga2(options)     ;                            % begin the optimization!
+
+
+% re-optimize using 30 finite volumes
+N = 30 ; 
+Function = @(x) FiveStepModSkarstromProcessSim( x, material, type, N ) ; % Function to simulate the PSA cycle
+
+options.objfun     = Function           ;                % objective function handle
+options.initfun    = {@initpop, result} ;                % Supply variables from previous results
+options.maxGen     = 120                ;                % populaion size
+options.outputfile = 'UTSA-16_Economic_2.txt'         ;
+result2            = nsga2(options)     ;                % begin the optimization!
+
+end
+

EconomicOptimization_v2.m

@@ -0,0 +1,51 @@
+clc
+format long
+parpool('local', 12);
+
+addpath('CycleSteps')
+addpath('GA_files')
+
+load('Params')
+
+N = 30 ;
+type = 'EconomicEvaluation' ;
+
+for i = 12:12
+
+% load parameters
+IsothermParams     = IsothermPar(i, :) ;    
+material_propertry = SimParam(i, :)    ;
+
+material    = {}                 ;
+material{1} = material_propertry ;
+material{2} = IsothermParams     ;
+
+Function = @(x) PSACycleSimulation( x, material, type, N ) ; % Function to simulate the PSA cycle
+
+% initial variables
+[~, vars] = sortt(loadpopfile('Ec.txt'));
+
+options            = nsgaopt();                          % create default options structure
+options.popsize    = 60;                                 % populaion size
+options.outputfile = 'Ec_2.txt';
+options.maxGen     = 120;                                % max generation
+
+options.vartype    = [1, 1, 1, 1, 1, 1] ;
+
+options.initfun={@Pop_Override, vars}   ;                % Supply variables from previous results
+
+options.numObj  = 2 ;                                    % number of objectives
+options.numVar  = 6 ;                                    % number of design variables
+options.numCons = 3 ;                                    % number of constraints
+options.lb = [1e5,  10, 0.01, 0.1, 0, 1e4]   ;           % lower bound of x
+options.ub = [10e5, 1000, 0.99, 2, 1, 5e4]   ;           % upper bound of x
+options.nameObj = {'-productivity','energy'} ;           % the objective names are showed in GUI window.
+options.objfun  = Function                   ;           % objective function handle
+
+options.useParallel = 'yes' ;                            % parallel computation is non-essential here
+options.poolsize     = 12   ;                            % number of worker processes
+
+result2 = nsga2(options)    ;                            % begin the optimization!
+
+end
+