Nonlinear Programming (NLP) Operation Research December 29, 2014 RS and GISc, IST, Karachi.
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Transcript of Nonlinear Programming (NLP) Operation Research December 29, 2014 RS and GISc, IST, Karachi.
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Nonlinear Programming (NLP)Nonlinear Programming (NLP)
Operation ResearchOperation ResearchDecember 29, 2014December 29, 2014
RS and GISc, IST, KarachiRS and GISc, IST, Karachi
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IntroductionIntroduction
• In LP, the goal is to maximize or minimize a linear function subject to linear constraints
• But in many real-world problems, either– objective function may not be a linear function, or – some of the constraints may be nonlinear
• Functions having exponents, logarithms, square roots, products of variables, and so on are nonlinear
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NLPNLP
• Optimization problems that involve nonlinear functions are called nonlinear programming (NLP) optimization
• Solution methods are more complex than linear programming methods
• Solution techniques generally involve searching a solution surface for high or low points requiring the use of advanced mathematics
• NLPs that do not have any constraints are called unconstrained NLPs
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Optimality Conditions: Unconstrained optimizationOptimality Conditions: Unconstrained optimization
• Can be solved using calculus
• For Z=f(X), the optimum occurs at the point where f '(X) =0 and f’''(X) meets second order conditions
– A relative minimum occurs where f '(X) =0 and f’''(X) >0
– A relative maximum occurs where f '(X) =0 and f’''(X) <0
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Concavity and Second DerivativeConcavity and Second Derivative
f’’(x)<0 f’’(x)>0 f’’(x)<0 f‘’(x)>0
local max andglobal max
local max
local min local min and global min
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Solution process is straightforward using calculus:
f'(x) = -2x + 9 Set this equal to zero and obtain x = 4.5
f''(x) = -2 which is negative at x = 4.5 (or at any other x-value) so we have indeed found a maximum ratherthan a minimum point
So the function is maximized when x = 4.5, with a maximum value of -4.52 + 9(4.5) + 4 = 24.25.
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Example: An unconstrained problem Example: An unconstrained problem
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ProblemProblem• One problem is difficulty in distinguishing
between a local and global minimum or maximum point
Local maximum
Global maximum
This is trickier: a value x whose first derivative is zero and whose second derivative is negative is not necessarily the solution point! It could be a local maximum point rather than the desired global maximum point.
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Feasible region
Solution point
In the case of this constrained optimization problem basic calculus is of no value, as the derivative at the solution point is not equal to zero
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ProblemsProblems
• Solutions to NLPs are found using search procedures
• Search can fail!!!
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NLP Example: Searches Can Fail!NLP Example: Searches Can Fail!
Maximize f(x) = x3 - 30x2 + 225x + 50
1010
The correct answer is that the problem is unbounded. There is no solution point!
Solvers may converge to a local maximum
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1111
Profit function, Z, with volume independent of price:
Z = vp - cf - vcv
where v = sales volume
p = price
cf = unit fixed cost
cv = unit variable cost
Add volume/price relationship:
v = 1,500 - 24.6p
Figure 1 Linear Relationship of Volume to Price
Example
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Profit, Z = 1,696.8p - 24.6p2 - 22,000
Figure 2 The Nonlinear Profit Function
With fixed cost (cf = $10,000) and variable cost (cv = $8):
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The slope of a curve at any point is equal to the derivative of the curve’s function.
The slope of a curve at its highest point equals zero.
Figure 3 Maximum profit for the profit function
Optimal Value of a Single Nonlinear Function= Maximum Point on a Curve
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Z = 1,696.8p - 24.6p2 -22,000
dZ/dp = 1,696.8 - 49.2p
= 0
p = 1696.8/49.2
= $34.49
v = 1,500 - 24.6p
v = 651.6 pairs of jeans
Z = $7,259.45 Figure 4 Maximum Profit, Optimal Price, and Optimal Volume
Optimal Value of a Single Nonlinear FunctionSolution Using Calculus
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If a nonlinear problem contains one or more constraints it
becomes a constrained optimization model
A nonlinear programming model has the same general form
as the linear programming model except that the objective
function and/or the constraint(s) are nonlinear.
Solution procedures are much more complex and no
guaranteed procedure exists for all NLP models.
Constrained Optimization in Nonlinear ProblemsDefinition
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Effect of adding constraints to nonlinear problem:
Figure 5 Nonlinear Profit Curve for the Profit Analysis Model
Constrained Optimization in Nonlinear ProblemsGraphical Interpretation (1 of 3)
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1717Figure 6 A Constrained Optimization Model
Constrained Optimization in Nonlinear ProblemsGraphical Interpretation (2 of 3)- First constrained p<= 20
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Figure 7 A Constrained Optimization Model with a Solution Point Not on the Constraint Boundary
Constrained Optimization in Nonlinear ProblemsGraphical Interpretation (3 of 3) Second constrained p<= 40
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1919
Unlike linear programming, solution is often not on the
boundary of the feasible solution space.
Cannot simply look at points on the solution space boundary
but must consider other points on the surface of the
objective function.
This greatly complicates solution approaches.
Solution techniques can be very complex.
Constrained Optimization in Nonlinear ProblemsCharacteristics
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2020
Centrally locate a facility that serves several customers or other facilities in order to minimize distance or miles traveled (d) between facility and customers.
di = sqrt[(xi - x)2 + (yi - y)2]
Where:(x,y) = coordinates of proposed facility(xi,yi) = coordinates of customer or location facility i
Minimize total miles d = diti
Where:di = distance to town i
ti =annual trips to town i
Facility Location Example ProblemProblem Definition and Data (1 of 2)
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2121
Coordinates Town x y Annual Trips Abbeville Benton Clayton Dunnig Eden
20 10 25 32 10
20 35 9
15 8
75 105 135 60 90
Facility Location Example ProblemProblem Definition and Data (2 of 2)
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Facility Location Example Problem: Using Excel SolverFacility Location Example Problem: Using Excel Solver
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Excel SolverExcel Solver
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2424Figure 13
Facility Location Example ProblemSolution Using Excel
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2525
Facility Location Example ProblemSolution Map
di = sqrt[(xi - x)2 + (yi - y)2]
dA=sqrt[(20- 20.668)2 + (20- 15.473)2]
dA=4.57........................................ dE=6.22
d = diti
d = 4.57(75)+................................+90(13.02)
d = 5583.8 total annual distance
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2626Rescue Squad Facility Location
Facility Location Example ProblemSolution Map
X = 20.668, Y = 15.473
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More ExamplesMore Examples
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