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Calculus-Based Optimization AGEC 317

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Title: Calculus-Based Optimization AGEC 317


1
Calculus-Based Optimization
AGEC 317 Economic Analysis for Agribusiness and
Management
2
Readings
  • Optimization Techniques

3
Why Consider Optimization?
  • Consumers maximize utility or satisfaction.
  • Producers or firms maximize profit or minimize
    costs.
  • Optimization is inherent to economists.

4
Setting-Up Optimization Problems
  • Define the agents goal objective function and
    identify the agents choice (control) variables
  • Identify restrictions (if any) on the agents
    choices (constraints). If no constraints exist,
    then we have unconstrained minimization or
    maximization problems.
  • If constraints exist, what type?
  • Equality Constraints (Lagrangian)
  • Inequality Constraints (Linear Programming)

5
  • Mathematically, Optimize y f(x1, x2, . . .
    ,xn)
  • subject to (s.t.)
  • gj (x1, x2, . . . ,xn) bj
  • or
  • bj j 1, 2, . . ., m.
  • or
  • bj
  • y f(x1, x2, . . . ,xn) ? objective function
  • x1, x2, . . . ,xn ? set of decision variables
    (n)
  • optimize ? either maximize or minimize
  • gi(x1, x2, . . . ,xn) ? constraints (m)

6
  • Constraints refer to restrictions on resources
  • legal constraints
  • environmental constraints
  • behavioral constraints

7
Review of Derivatives
  • yf(x) First-order condition
  • Second-order condition
  • Constant function
  • Power function
  • Sum of functions
  • Product rule
  • Quotient rule
  • Chain rule


8
Unconstrainted UnivariateMaximization Problems
max f(x)
  • Solution
  • Derive First Order Condition (FOC) f(x)0
  • Check Second Order Condition (SOC) f(x)lt0
  • Local vs. global If more than one point satisfy
    both FOC and SOC, evaluate the objective function
    at each point to identify the maximum.

9
Example
  • PROFIT -40 140Q 10Q2
  • Find Q that maximizes profit
  • 140 20Q set 0
  • Q 7
  • - 20 lt 0
  • max profit occurs at Q 7
  • max profit -40 140(7) 10(7)2
  • max profit 450

10
Minimization Problems Min f(x)
  • Solution
  • Derive First Order Condition (FOC) f(x)0
  • Check Second Order Condition (SOC) f(x)gt0
  • Local vs. global If more than one point satisfy
    both FOC and SOC, evaluate the objective function
    at each point to identify the minimum.

11
Example
  • COST 15 - .04Q .00008Q2
  • Find Q that minimizes cost
  • -.04 .00016Q set 0
  • Q 250
  • .00016 gt 0
  • Minimize cost at Q 250
  • min cost 10

12
Unconstrained Multivariate Optimization
  • Min
  • FOC
  • SOC
  • Max
  • FOC
  • SOC

13
Example
  • PROFIT is a function of the output of two
    products
  • (e.g.heating oil and gasoline)
  • Q1 Q2
  • so,
  • Solve Simultaneously Q1 5.77 units
  • Q2 4.08 units

14
Second-Order Conditions
(-20)(-16) (-6)2 gt 0 320 36 gt 0 we
have maximized profit.
15
Constrained Optimization
  • Solution Lagrangian Multiplier Method
  • Maximize y f(x1, x2, x3, , xn)
  • s.t. g(x1, x2, x3, , xn) b
  • Solution
  • Set up Lagrangian
  • FOC

16
Lagrangian Multiplier
  • Interpretation of Lagrangian Multiplier ? the
    shadow value of the constrained resource.
  • If the constrained resource increases by 1 unit,
    the objective function will change by ? units.

17
Example
Maximize Profit subject to (s.t.) 20Q1 40Q2
200 Could solve by direct
substitution Note that 20Q1 200 40Q2
or Q1 10 2Q2 Maximize Profit
Combine like terms. Maximize Profit

18
Lagrangian Multiplier Method
19
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