Alkylation Process Optimization

TomSym implementation of GAMS Example (PROCESS,SEQ=20)

Optimization of a alkylation process.

Bracken, J, and McCormick, G P, Chapter 4. In Selected Applications of Nonlinear Programming. John Wiley and Sons, New York, 1968.

olefin: olefin feed (bpd)

isor: isobutane recycle (bpd)

acid: acid addition rate (1000lb per day)

alkylate: alkylate yield (bpd)

isom: isobutane makeup (bpd)

strength: acid strength (weight pct)

octane: motor octane number

ratio: isobutane makeup to olefin ratio

dilute: acid dilution factor

f4: f-4 performance number

toms olefin isor acid alkylate isom strength octane ratio dilute f4
x = [olefin isor acid alkylate isom strength octane ratio dilute f4]';

% Variables are positive
cbnd = {x >= 0};

% Alkylate yield definition
eq1 = {alkylate == olefin*(1.12+.13167*ratio-.00667*(ratio^2))};

% Isobutane makeup definition
eq2 = {1.22*alkylate == olefin + isom};

% Acid strength definition
eq3 = {acid == alkylate*dilute*strength/(98-strength)/1000};

% Motor octane number
eq4 = {octane == 86.35+1.098*ratio-.038*(ratio^2)-.325*(89-strength)};

% Isobutane to olefin ratio
eq5 = {ratio == (isor+isom)/olefin};

% Dilution definition
eq6 = {dilute == 35.82 - .222*f4};

% f-4 definition
eq7 = {f4 == -133 + 3*octane};

% Profit definition
profit = .063*alkylate*octane - 5.04*olefin -...
    .035*isor - 10*acid - 3.36*isom;

% Ranged alkylate yield definition
rangey = olefin*(1.12+.13167*ratio-.00667*(ratio^2))/alkylate;

% Ranged motor octane number
rangem = (86.35+1.098*ratio-.038*ratio^2-.325*(89-strength))/octane;

% Ranged dilution definition
ranged = (35.82 - .222*f4)/dilute;

% Ranged f-4 definition
rangef = (-133 + 3*octane)/f4;

% Bounds
eq8 = {0.9 <= rangey <= 1.1
    0.9 <= rangem <= 1.1
    0.9 <= ranged <= 1.1
    0.9 <= rangef <= 1.1};

eq9 = {85 <= strength <= 93
    90 <= octane <= 95
    3 <= ratio <= 12
    1.2 <= dilute <= 4
    145 <= f4 <= 162
    10 <= olefin <= 2000
    isor <= 16000
    acid <= 120
    alkylate <= 5000
    isom <= 2000};

% Starting point
x0 = {olefin == 1745; isor == 12000
    acid == 110; alkylate == 3048; isom == 1974;
    strength == 89.2; octane == 92.8;
    ratio == 8; dilute == 3.6; f4 == 145};

con1 = {cbnd; eq1; eq2; eq3; eq4; eq5; eq6; eq7; eq9};
solution1 = ezsolve(-profit,con1,x0);

con2 = {cbnd; eq2; eq3; eq5; eq8; eq9};
solution2 = ezsolve(-profit,con2,x0);

Problem type appears to be: qpcon
===== * * * =================================================================== * * *
TOMLAB - Tomlab Optimization Inc. Development license  999001. Valid to 2010-02-05
=====================================================================================
Problem: ---  1: Problem 1                      f_k   -1161.336602887075100000
                                       sum(|constr|)      0.000000052216478680
                              f(x_k) + sum(|constr|)  -1161.336602834858500000
                                              f(x_0)   -872.387200000001030000

Solver: snopt.  EXIT=0.  INFORM=1.
SNOPT 7.2-5 NLP code
Optimality conditions satisfied

FuncEv    1 ConstrEv   27 ConJacEv   27 Iter   25 MinorIter   34
CPU time: 0.031250 sec. Elapsed time: 0.031000 sec. 
Problem type appears to be: qpcon
===== * * * =================================================================== * * *
TOMLAB - Tomlab Optimization Inc. Development license  999001. Valid to 2010-02-05
=====================================================================================
Problem: ---  1: Problem 1                      f_k   -2410.828271690259500000
                                       sum(|constr|)      0.000000054132116436
                              f(x_k) + sum(|constr|)  -2410.828271636127300000
                                              f(x_0)   -872.387200000001030000

Solver: snopt.  EXIT=0.  INFORM=1.
SNOPT 7.2-5 NLP code
Optimality conditions satisfied

FuncEv    1 ConstrEv    9 ConJacEv    9 Iter    8 MinorIter   24
CPU time: 0.015625 sec. Elapsed time: 0.015000 sec.