* BATCHSPC
* OPTIMAL DESIGN OF MULTIPRODUCT BATCH
PLANTS
* SINGLE PRODUCT CAMPAIGNS
* G. Kocis, V. Voudouris and I. E.
Grossmann
** Department of Chemical Engineering,
Carnegie Mellon University
* Pittsburgh, PA 15213, U.S.A.
*
* Ref: I&EC RESEARCH, 1992, Vol. 31,
No. 5, pp. 1315-1325.
*
* MILP FORMULATION OF BATCH PROCESSING
PROBLEM
*
SETS I products
/a,
b,
c/
J stages
/mixer,
reactor,
centrifuge/
K max number of units in parallel /1*3/
S number of different standard sizes
/1*3/
SK combine sets s and k /1*9/;
SCALARS H horizon time (hrs) /6000/
PARAMETERS
Q(i) demand of product i (kg)
/a = 100000,
b = 200000,
c = 50000/
ALPHA(j) cost coefficient for batch units
/mixer = 250,
reactor = 300,
centrifuge = 400/
BETA(j) cost exponent for batch units
/mixer = 0.60,
reactor = 0.70,
centrifuge = 0.70/
DELTA(j) fixed cost for batch units ($
per year)
/mixer = 1000,
reactor = 2000,
centrifuge = 3000/
VLOW(j) lower bound for size of batch
unit (lt)
/mixer = 250,
reactor = 250,
centrifuge = 250/
VUPP(j) upper bound for size of batch
unit (lt)
/mixer = 2500,
reactor = 2500,
centrifuge = 2500/
NUP(j) upper bound for N
/mixer = 3,
reactor = 3,
centrifuge = 3/
SIZE(s) equipment sizes
/1 = 1000
2 = 1500
3 = 2000/
TABLE SF(I,J) SIZE FACTOR FOR PRODUCT i
IN STAGE j (LT PER Kg)
mixer reactor centrifuge
a 2.1 3.2 2.2
b 2.2 3.4 2.8
c 3.1 2.4 2.9
TABLE T(I,J) PROCESSING TIME OF PRODUCT i
IN STAGE j (hrs)
mixer reactor centrifuge
a 4 8 5
b 5 9 6
c 6 10 4; |
