Senin, 26 September 2011

OPTIMATION ENGINEERING : LINEAR PROGRAM MODELLING OF SEGO NJAMOER (1)




Hello guys, i'm back. Today i'd like to share how to create mathematical modelling for optimation purpose. In optimations, some factors need to be calculated to obtain the maximum or minimum point. 

INTRODUCTIONS

Sego Njamoer is a snack made from rice and mushroom served in onigiri style. The word Sego Njamoer comes from Javanesse language means Mushroom Rice. Sego Njamoer also being used as trademark of the company owned by Njamoer Management, established in 2009 by Mahendra Ega Higuitta, Young Entrepreneur and student of Engineering Physics Department Sepuluh Nopember Institute of Technology. With many innovations, Sego Njamoer has collected many achievements and award in business competitions, such as LA Business contest, PIMNAS 24, Shell eco wire, and many others.
 Production House of Sego Njamoer addressed in Gebang Wetan, stored main ingerdients of the product : Rice and Mushroom, storedhouse of the package, plastic spoon, and product seasoning (such as flour, salt, pepper, etc). Not only for warehouse, PH also used as outlet that sell Sego Njamoer Product.






Figure 1 Sego njamoer and its mascot (called Jembi)
Since June 2011, Sego Njamoer owned nine outlets in Surabaya. Four outlets located in ITS area (Ria Swalayan, BEM FTI, Center Canteen, and Gebang), and the others are located in Faculty of Medicine Airlangga University (Unair A), Faculty of Economy and Business Airlangga University (Unair B), Surabaya State University (Unesa), Stella Maris Senior High School (SMA Stella Maris), and Computer High School (Stikom).  Based on managers data report, each outlet has different average amount demand in each day. Highest demand of the product is in BEM FTI outlet with 350 product per day. Followed by Unair A (260 portions), Outlet with the lowest demand is SMA Stella Maris which is 80 products. Complete report of each Sego Njamoer daily demand are listed in Table 1 below :



Figure 2 Map of sego njamoer outlet

Table 1 List of product average demand for each outlet
No
Outlet
Average demand in one day
1
Ria Swalayan
150
2
BEM FTI
350
3
Center Canteen
200
4
Gebang
200
5
Unair A
260
6
Unair B
150
7
Unesa
100
8
SMA Stella Maris
80
9
Stikom
150

Main ingerdients (rice and mushroom) is not produced by the company. Rice are collected from many food stall, and mushroom is providable from market. Based on main ingerdients supply, maximum product that can be served and selled are 1500 portions. Package of the prduct ordered from print shop which is printed 100.000 packages per month. Fuel cost is one variable that should be calculated because some outlet is far from production house. Fuel cost for each oulet is shown in Table 2

Table 2 Daily fuel cost for each oulet
No
Outlet
Fuel cost per day (x1000 rupiahs)
1
Ria Swalayan
1
2
BEM FTI
1
3
Center Canteen
1
4
Gebang
0
5
Unair A
3
6
Unair B
3
7
Unesa
5
8
SMA Stella Maris
10
9
Stikom
4

Based on the explanation above, how to obtain the maximum profit in one day?

SOLUTIONS :

Maximum supply in 1 day :
1500 products

Income in one day based on maximum supply :
1500 x 3000 = 4.500.000 = 4.500  (x1000)

Package ordered in 1 month are 100.000 packages, assume that there are 30 days in one month

Objective : How to obtain the maximum profit in 1 day?

Modeling :

Step 1 : Decision Variables :
Let xi = Amount of product selled in each outlet (i)
x1 = Ria Swalayan
x2 = BEM FTI
x3 = Center Canteen
x4 = Gebang
x5 = Unair A
x6 = Unair B
x7 = Unesa
x8 = SMA Stella Maris
x9 = Stikom

Step 2 : Objective Functions Maximize profit per each day :
z = x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9

Step 3 : Define the Constrains :
Maximum demand in each outlet
x1 <  150
x2 <  350
x3 <  200
x4 <  200
x5 <  260
x6 <  150
x7 <  100
x8 <  80
x9 150

Maximum product that can be supplied :
x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8  + x<  1500

Fuel cost for each outlet (fuel cost greater than income is not allowed) :
x1 + x2 + x3  + 3x5 + 3x6 +5x7 +10x+4x<  4200

Maximum package :
30 (x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9) < 100.000

Each variable should be positive
x1 > 0
x2 > 0
x3 > 0
x4 > 0
x5 > 0
x6 > 0
x7 > 0
x8 >  0
x9  >  0

Complete model :
z(xi) = x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9

x1 150
x2 350
x3 200
x4 200
x5 260
x6 150
x7 100
x8 80
x9 150

x1 + x2 + x3 + x4 + x5 + x6 + x7 + x+ x<  1500

x1 + x2 + x3  + 3x5 + 3x6 +5x7 +10x+4x<  4200

3(x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9) < 10.000

x1 > 0
x2 > 0
x3 > 0
x4 > 0
x5 > 0
x6 > 0
x7 > 0
x8 >  0
x9  >  0


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