5) Optimal solution - is the solution that maximizes or minimizes the objective function while satisfying all the constraints. It is the best possible solution for the given problem.
In the example given, an optimal solution would be values for X1, X2, and X3 that maximize the objective function (profit) while satisfying the system constraints (2X1 + 3X2 + 6X3 ≤ 300, 5X1 + X2 + 2X3 ≤ 200, 3X1 + 5X2 + 2X3 ≤ 360) and individual constraints (X1 = 30, X2 ≥ 4) as well as the non-negativity constraints (X1, X2, X3 ≥ 0).
Cont’d
4) Parameters - are fixed values that specify the impact that one unit of each decision variable will have on the objective. Example:
Maximize: 4X1 + 7X2 + 5X3 (Profit) objective function
Subject to:
2X1 + 3X2 + 6X3 300
5X1 + X2 + 2X3 200 System constraints
3X1 + 5X2 + 2X3 360
X1 = 30
X2 4 Individual constraints
X1, X2, X3 0 Non-negativity constraints
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