Abstract
The core problem in this case was related with a production planning again. How many S and how many P can I produce in order to maximize my profit with production's constraints like limited raw materials (USB ports), limited assembly hours and limited quality control hours. The main lesson of this case is graphical application and interpretation of linear programming method in order to search the optimal solution.
Make or buy:
In this case, things are more complicated because we had to determine how much to produce of each product and how much to buy of each same product (with a total units pre-defined) in order to minimize total cost (production' cost + purchase's cost). There were two types of constraints: productions' constraints and purchase's constraints. The mean shrewdness of this case is to name A, B, C, D, E production' units and A', B', C', D', E' purchasing' units in order to differentiate sources of units and constraints related in the same time.
Reallocating vehicles:
This case was a problem of re-distribution. The decision variable was how many bikes we need to move from X to Y (with a total of 8 different bike' stations). The objective was to minimize transportations cost. The number of bike had to correspond with a number of place pre-determined. It was constraints.
In this exercise, we have seen it exists two ways to solve the problem with two different answers. The manner to write the problem can influence your solution. It is essential to analyze your model after the resolution.
