Linear optimization: Mathematical formulations of problems presented in the course 1: Unterschied zwischen den Versionen
[unmarkierte Version] | [unmarkierte Version] |
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− | + | x = number of units of X produced in the current week | |
− | + | ||
+ | y = number of units of Y produced in the current week | ||
Constraints: | Constraints: | ||
− | <math>50x + 24y \leq 40</math> machine | + | <math>50x + 24y \leq 40*60\rightarrow</math> machine time A: 50 minutes per product x and 24 minutes per product y has to be lower than the capacity of 40 hours of machine A. |
− | <math>30x + 33y \leq 35</math> machine | + | <math>30x + 33y \leq 35*60\rightarrow</math> machine time B: 30 minutes per product x and 33 minutes per product y has to be lower than the capacity of 35 hours of machine B. |
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− | <math> | + | <math>x \geq (75 - 30)</math> <math>\rightarrow x \geq 45</math> so production of X <math>\geq</math> demand (75) - initial stock (30) , which ensures we meet demand |
− | + | <math>y \geq 95 - 90</math> <math>\rightarrow y \geq 5</math> so production of Y <math>\geq </math> demand (95) - initial stock (90) , which ensures we meet demand | |
− | objective function: <math>max (x+30-75) + (y+90-95 | + | objective function: <math>max (x+30-75) + (y+90-95)</math> |
i.e. to maximise the number of units left in stock at the end of the week | i.e. to maximise the number of units left in stock at the end of the week |
Version vom 19. Juni 2013, 15:18 Uhr
Mathematical formulations of problems presented in the course
Example:
A company makes two products (X and Y) using two machines (A and B). Each unit of X that is produced requires 50 minutes processing time on machine A and 30 minutes processing time on machine B. Each unit of Y that is produced requires 24 minutes processing time on machine A and 33 minutes processing time on machine B.
At the start of the current week there are 30 units of X and 90 units of Y in stock. Available processing time on machine A is forecast to be 40 hours and on machine B is forecast to be 35 hours.
The demand for X in the current week is forecast to be 75 units and for Y is forecast to be 95 units. Company policy is to maximise the combined sum of the units of X and the units of Y in stock at the end of the week.
x = number of units of X produced in the current week
y = number of units of Y produced in the current week
Constraints:
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): 50x + 24y \leq 40*60\rightarrow
machine time A: 50 minutes per product x and 24 minutes per product y has to be lower than the capacity of 40 hours of machine A.
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): 30x + 33y \leq 35*60\rightarrow
machine time B: 30 minutes per product x and 33 minutes per product y has to be lower than the capacity of 35 hours of machine B.
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): x \geq (75 - 30)
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \rightarrow x \geq 45 so production of X Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \geq demand (75) - initial stock (30) , which ensures we meet demand
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): y \geq 95 - 90
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \rightarrow y \geq 5 so production of Y Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \geq demand (95) - initial stock (90) , which ensures we meet demand
objective function: Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): max (x+30-75) + (y+90-95)
i.e. to maximise the number of units left in stock at the end of the week