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27C0100
Tools  for  Business  Decisions
            Exercises
  kari.silvennoinen@student.hse.fi
Exam
• March  4th  or  May  18th

• Remember  to  register  for  the  exam  at  least  a  
  week  in  advance.




                      kari.silvennoinen@student.hse.fi      2
Ex  Set  4:  Eve  and  Steven
• Eve  does  MarkeJng  and  Dish  washing,  Steven  
  does  Cooking  and  Laundry
 Em       Ec       Ed       El          Sm          Sc         Sd        Sl
      1        0        1         0           0          1          0          1
   4,5     7,8      3,6          2,9       4,9        7,2         4,3         3,1   18,4
      1        1        1         1                                                   2=   2
                                              1          1          1          1      2=   2
      1                                       1                                       1=   1
               1                                         1                            1=   1
                        1                                           1                 1=   1
                                  1                                            1      1=   1



                                       kari.silvennoinen@student.hse.fi                         3
Ex  Set  4:  Peterson  and  Johnson

P1       P2         P3              P4               P5
     1          0          1                1                0
     1        1,8        1,6              0,8              1,4   3,4
     6         12         10                4                8   20 <=        20


P1       P2         P3              P4               P5
     1         0           1                0               0    2,6     16
     1         0           0                1               1    3,2     18
     1         0           1                1               0    3,4     20
     0         0           1                1               1    3,8     22
     1         0           1                0               1      4     24
     0         1           1                1               0    4,2     26
     1         0           1                1               1    4,8     28
     1         1           0                1               1      5     30


                         kari.silvennoinen@student.hse.fi                       4
Case  2
• Total  cost  goes  down  from  11,2  M$  to  9,9  M$
Amount of malt shipped from plant i to brewery j in year 1 (1000 ton)
                     Istanbul          Ankara             Total           Capacity

Afyon                 24,24              24              30,00            30,00
Konya                   0                 0              18,24            68,00
Import                  0                 0               0,00            20,00
Total malt            24,24              24
Total beer             202              200         (Million lt)


Amount of beer shipped from brewery j to distribution center k in year 1 (Million liters)
                     Istanbul           Izmir            Antalya           Bursa            Kayseri    Export (Izmir)        Total       Capacity

Istanbul               103               26                 0               60                0             13               202          220
Ankara                  0                48                50                0               102             0              200,00        200
Total                  103               74                50                60              102            13
Demands                103               74                50               60               102            13


                                                                                                      Total shipping cost                     9,935
                                                                                                                                     (Million dollars)




                                                          kari.silvennoinen@student.hse.fi                                                           5
What  next?
• What  if  more  decision  makers?
   – Different  values  and  priori1es
   – Different  objec1ves!  
• What  if  no  mathemaJcal  objecJve  funcJon?
   – F.e.  design  of  a  car


• In  real  world,  many  problems  are  complex.


                          kari.silvennoinen@student.hse.fi   6
OpJmizaJon
•   Step  1:  Need  for  op-miza-on  
•   Step  2:  Choose  decision  variables
•   Step  3:  Formulate  constraints  
•   Step  4:  Formulate  objec1ve  func1ons  
•   Step  5:  Set  up  variable  bounds  
•   Step  6:  Choose  an  op1miza1on  algorithm  
•   Step  7:  Obtain  solu1on(s)  
•   Step  8:  If  not  sa-sfied,  move  to  a  suitable  step  
    above.  
                                                           Deb,  2008

                         kari.silvennoinen@student.hse.fi                7
Excel  as  a  decision  tool
• In  the  real  world,  Excel  is  probably  the  most  (ab)
  used  tool  for  decision  making,
   – Probably  because  it’s  installed  prac1cally  everywhere
   – There’s  nothing  wrong  in  using  Excel,  but  be  aware  of  
     the  limita1ons
• Many  add-­‐ins  provide  more  func1onality  (f.e.  
  Crystal  Ball)
• Depending  on  your  needs,  R,  SAS  and  many  other  
  may  give  you  beZer  tools  than  Excel  to  analyze  and  
  solve  your  problems.
                          kari.silvennoinen@student.hse.fi               8
Extending  Excel
• Macros  are  not  (usually)  necessary,  but…
• Current  versions  of  Excel  support  Visual  Basic  
  for  ApplicaJons  (VBA),  but  more  powerful  
  VB.NET  is  also  an  opJon
   – If  you  want  to  do  serious  Excel-­‐programming,  learn  
     VB.NET  (or  C#.NET)  instead
   – If  interested,  as  a  student  you  can  get  Microso^’s  
     development  tools  for  free  at  
     hZps://downloads.channel8.msdn.com/    
                        kari.silvennoinen@student.hse.fi          9

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Exercises 6 - Tools for Business Decisions

  • 1. 27C0100 Tools  for  Business  Decisions Exercises kari.silvennoinen@student.hse.fi
  • 2. Exam • March  4th  or  May  18th • Remember  to  register  for  the  exam  at  least  a   week  in  advance. kari.silvennoinen@student.hse.fi 2
  • 3. Ex  Set  4:  Eve  and  Steven • Eve  does  MarkeJng  and  Dish  washing,  Steven   does  Cooking  and  Laundry Em Ec Ed El Sm Sc Sd Sl 1 0 1 0 0 1 0 1 4,5 7,8 3,6 2,9 4,9 7,2 4,3 3,1 18,4 1 1 1 1 2= 2 1 1 1 1 2= 2 1 1 1= 1 1 1 1= 1 1 1 1= 1 1 1 1= 1 kari.silvennoinen@student.hse.fi 3
  • 4. Ex  Set  4:  Peterson  and  Johnson P1 P2 P3 P4 P5 1 0 1 1 0 1 1,8 1,6 0,8 1,4 3,4 6 12 10 4 8 20 <= 20 P1 P2 P3 P4 P5 1 0 1 0 0 2,6 16 1 0 0 1 1 3,2 18 1 0 1 1 0 3,4 20 0 0 1 1 1 3,8 22 1 0 1 0 1 4 24 0 1 1 1 0 4,2 26 1 0 1 1 1 4,8 28 1 1 0 1 1 5 30 kari.silvennoinen@student.hse.fi 4
  • 5. Case  2 • Total  cost  goes  down  from  11,2  M$  to  9,9  M$ Amount of malt shipped from plant i to brewery j in year 1 (1000 ton) Istanbul Ankara Total Capacity Afyon 24,24 24 30,00 30,00 Konya 0 0 18,24 68,00 Import 0 0 0,00 20,00 Total malt 24,24 24 Total beer 202 200 (Million lt) Amount of beer shipped from brewery j to distribution center k in year 1 (Million liters) Istanbul Izmir Antalya Bursa Kayseri Export (Izmir) Total Capacity Istanbul 103 26 0 60 0 13 202 220 Ankara 0 48 50 0 102 0 200,00 200 Total 103 74 50 60 102 13 Demands 103 74 50 60 102 13 Total shipping cost 9,935 (Million dollars) kari.silvennoinen@student.hse.fi 5
  • 6. What  next? • What  if  more  decision  makers? – Different  values  and  priori1es – Different  objec1ves!   • What  if  no  mathemaJcal  objecJve  funcJon? – F.e.  design  of  a  car • In  real  world,  many  problems  are  complex. kari.silvennoinen@student.hse.fi 6
  • 7. OpJmizaJon • Step  1:  Need  for  op-miza-on   • Step  2:  Choose  decision  variables • Step  3:  Formulate  constraints   • Step  4:  Formulate  objec1ve  func1ons   • Step  5:  Set  up  variable  bounds   • Step  6:  Choose  an  op1miza1on  algorithm   • Step  7:  Obtain  solu1on(s)   • Step  8:  If  not  sa-sfied,  move  to  a  suitable  step   above.   Deb,  2008 kari.silvennoinen@student.hse.fi 7
  • 8. Excel  as  a  decision  tool • In  the  real  world,  Excel  is  probably  the  most  (ab) used  tool  for  decision  making, – Probably  because  it’s  installed  prac1cally  everywhere – There’s  nothing  wrong  in  using  Excel,  but  be  aware  of   the  limita1ons • Many  add-­‐ins  provide  more  func1onality  (f.e.   Crystal  Ball) • Depending  on  your  needs,  R,  SAS  and  many  other   may  give  you  beZer  tools  than  Excel  to  analyze  and   solve  your  problems. kari.silvennoinen@student.hse.fi 8
  • 9. Extending  Excel • Macros  are  not  (usually)  necessary,  but… • Current  versions  of  Excel  support  Visual  Basic   for  ApplicaJons  (VBA),  but  more  powerful   VB.NET  is  also  an  opJon – If  you  want  to  do  serious  Excel-­‐programming,  learn   VB.NET  (or  C#.NET)  instead – If  interested,  as  a  student  you  can  get  Microso^’s   development  tools  for  free  at   hZps://downloads.channel8.msdn.com/     kari.silvennoinen@student.hse.fi 9