Question 1:

(i) Analysis Stage:

(a) Inventory  -  an enterprise must take inventory of all the hardware and
software that they use in their operations and identify all the date-sensitive
materials (applications and data files) within that inventory.  As well, the
size and complexity of the components which are likely to be affected can be
determined.
				
(b) Risk Assessment - both internal and external impact analysis should be
performed to determine the costs and liability associated with the problems
caused by Y2K.  External affiliations will also face similar problems, and
should be considered if they are essential to internal operations.  From
this analysis an estimate of the magnitude of the change in effort required
to fix the problem can be developed (ie. how many lines of code are affected,
what additional components are affected such as  hardware and inter-
organizational systems)

(ii) Synthesis Stage:
		
(a) Conversion - replacing appropriate source code, updating databases and
files, and expanding year fields.

(b) Testing and Implementing Solutions- Every modified system and its
interfaces must be tested with year data before and after the year 2000.



Question 2:

Define  X1: the fraction of Method 1 (increasing the stack heights) used;
        X2: the fraction of Method 2 (using filters) used;
        X3: the fraction of Method 3 (using better fuel) used.

Then the LP problem can be formulated as the following:

Minimize        Z = 8X1 + 7X2 + 11X3
subject to
                12X1 + 25X2 + 17X3 >= 30
                35X1 + 18X2 + 56X3 >= 80
                37X1 + 28X2 + 29X3 >= 60
                  X1               <= 1
                         X2        <= 1
                                X3 <= 1
                        X1, X2, X3 >= 0



Question 3:

You must submit your graph.  From the graph, it can be seen that the optimal
solution is achieved at the intersection of
                 X1 + X2 = 8
                2X1 - X2 = 10.
By solving this system of equations, we find the optimal solution is
(X1, X2) = (6, 2).  The optimal objective value is 3X1 + 2X2 = 22.



Question 4:

First of all, we can neglect the market strategy M2, since it is dominated
by the other strategies.  New table can be constructed as follows;

	S1(0.2)	S2(0.3)	S3(0.4)	S4(0.1)
M1	-20	140	90	220
M3	40	100	200	120
M4	60	110	100	200

(a) The most probable sales level corresponds to S3, with the probability of
0.4.  With this approach our decision will be M3 since it earns most for the
sales level of S3.

(b) The expected values of each machine can be determined as follows:
	M1 = ((-20)*0.2+140*0.3+90*0.4+220*0.1) * 1000 	= $ 96,000
	M3 = (40*0.2+100*0.3+200*0.4+120*0.1) * 1000 	= $ 130,000
	M4 = (60*0.2+110*0.3+100*0.4+200*0.1) * 1000 	= $ 105,000
So our decision will be M3.

(c) Since we are using the laplace criterion we will assume the nature to be
indifferent, and assign the probabiltiy of 1/n, (which corresponds to 1/4
for this problem) to each future.  So we wil look at the average profit for
each machine such as
	M1 = ((-20)+140+90+220) * 1000*0.25 	= $107,500
	M3 = (40+100+200+120) * 1000 *0.25	= $ 115,000
	M4 = (60+110+100+200) * 1000 *0.25	= $ 117,500
So our decision would be M4.

(d) Maximum profits and minimum profits for each machine is as follows
        Alternative     Max     Min
        M1              220     -20
        M3              200     40
        M4              200     60
So our Maximin decision would be M4.

(e) For the Hurwicz rule, alpha = 0.4.
        Alternatives     Values of the equation
        M1              (0.4*220+0.6*(-20))*1000= 76,000
        M3              (0.4*200+0.6*40)*1000= 104,000
        M4              (0.4*200+0.6*60)*1000= 116,000
So our decision would be M4.