Free Online Flashcard Deck

5 Optimization and Decision Models Free Online FlashCards

Study 5 Optimization and Decision Models with 12 free online flashcards. Review key terms, definitions, and concepts with this interactive flashcard deck.

12 cards
01
Front

What are the four components of an optimization model?

Back

The four parts are decision variables, an objective function, constraints, and the feasible region.

02
Front

What makes a solution feasible?

Back

A feasible solution satisfies every constraint, including restrictions such as nonnegativity.

03
Front

What is the objective function?

Back

The objective function is the quantity being maximized or minimized, such as profit, cost, time, area, or risk.

04
Front

What is the correct order for formulating an applied model?

Back

A valid model defines variables and units, states the objective, translates limitations into constraints, determines the domain, solves candidates, and interprets the result.

05
Front

What dimensions maximize the three-sided garden’s area?

Back

For the garden, A(x)=100x−2x2A(x)=100x-2x^2 on [0,50][0,50]. The maximum is 1250 m21250\text{ m}^2 at x=25 mx=25\text{ m} and y=50 my=50\text{ m}.

06
Front

How is an interior critical point identified?

Back

An interior critical point occurs where fx=fy=0f_x=f_y=0, or where at least one partial derivative does not exist.

07
Front

What does the second-derivative test conclude when D<0D<0?

Back

With D=fxxfyy−(fxy)2D=f_{xx}f_{yy}-(f_{xy})^2, D<0D<0 indicates a saddle point; D>0D>0 uses the sign of fxxf_{xx} to distinguish a local minimum or maximum.

08
Front

What must boundary analysis include?

Back

For a closed, bounded region, check interior critical points, every boundary component, boundary critical points, endpoints, and corners.

09
Front

Where are the extrema of x+yx+y on the triangular region?

Back

For f(x,y)=x+yf(x,y)=x+y with x≥0x\geq0, y≥0y\geq0, and x+y≤10x+y\leq10, the maximum is 1010 on the boundary x+y=10x+y=10, and the minimum is 00 at (0,0)(0,0).

10
Front

What equations define Lagrange-multiplier candidates?

Back

For an equality constraint g(x,y)=cg(x,y)=c, solve ∇f=λ∇g\nabla f=\lambda\nabla g together with g(x,y)=cg(x,y)=c.

11
Front

What is the geometric meaning of Lagrange multipliers?

Back

At a constrained optimum, the objective’s level curve is tangent to the constraint curve, so their gradients are parallel.

12
Front

What rectangle maximizes area for fixed perimeter?

Back

With fixed perimeter PP, the rectangle of greatest area is a square: x=y=P/4x=y=P/4.