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Questions

Question 1

What is the first step in formulating an optimization problem?

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Question 2

According to Table 12.1, which of the following is typically an objective to be minimized in design optimization?

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Question 3

What is the source of equality constraints in an optimization model?

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Question 4

In a constrained optimization problem, what is an 'active' constraint?

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Question 5

In the optimization of process heat recovery, what is the typical range for the optimum minimum temperature approach, DToptimum?

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Question 6

What is the fundamental trade-off when optimizing the degree of process heat recovery?

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Question 7

Why might optimizing a subcomponent of a process, like a single distillation column, not lead to the optimum design for the whole process?

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Question 8

In a single-variable optimization problem, what does a second derivative of the objective function that is less than zero at a stationary point indicate?

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Question 9

The golden-section search is a single-variable search method that is more computationally efficient than a regular search if the desired precision fraction, epsilon, is below what value?

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Question 10

The golden-section search method reduces the search range to what fraction of the original range with each new point added?

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Question 11

What is the primary challenge associated with multivariable optimization problems that have a nonconvex feasible region?

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Question 12

In a linear programming (LP) problem, where is the optimal solution guaranteed to be located?

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Question 13

What is the role of slack and surplus variables in the SIMPLEX algorithm for linear programming?

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Question 14

For a highly nonlinear programming (NLP) problem with fewer than 50 variables where gradients must be found numerically, which solution method is suggested as the best?

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Question 15

What is a significant limitation of the successive linear programming (SLP) method for solving nonlinear problems?

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Question 16

In optimization problems, what is the purpose of introducing binary integer variables?

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Question 17

What is the name of the algorithm commonly used for solving mixed-integer problems that works by treating integer variables as continuous and then systematically partitioning the problem?

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Question 18

Which of the following is cited as a reason why few industrial designs are rigorously optimized?

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Question 19

In the distillation column optimization in Example 12.1, what was the total annualized cost (TAC) for the initial guess of 40 trays with the feed on tray 20?

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Question 20

What was the 'soft constraint' on the column height in the optimization of the distillation column in Example 12.1?

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Question 21

In Example 12.1, what was the final optimized design for the distillation column in terms of the number of trays and feed tray location?

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Question 22

What was the final total annualized cost for the optimized distillation column design of 80 trays with feed on tray 27 in Example 12.1?

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Question 23

When investigating the feasibility of a 120-tray column in Example 12.1, what installation factor was used for the column shell to account for the higher cost of using larger cranes?

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Question 24

In an optimization problem expressed as 'Optimize z = f(x)', what does the function f(x) represent?

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Question 25

An optimization problem is described as 'unbounded' when what condition occurs?

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Question 26

If an optimization problem has 'n' variables and 'me' equality constraints, how are the degrees of freedom determined?

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Question 27

The quasi-Newton method is an indirect search method that finds an optimum by searching for a point that satisfies which condition?

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Question 28

In the steepest descent method for multivariable optimization, what determines the search direction from the current point?

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Question 29

What is a 'degenerate' linear programming (LP) problem?

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Question 30

For which type of nonlinear programming (NLP) problems are reduced gradient methods noted to be particularly effective?

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Question 31

What is the goal of superstructure optimization in process synthesis?

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Question 32

In Example 12.1, what rule of thumb was applied to convert the installed capital cost of the distillation column into an annual capital charge?

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Question 33

What were the specified costs per Gigajoule (GJ) for heating and cooling utilities in the distillation column optimization of Example 12.1?

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Question 34

In the second iteration of the distillation column optimization in Example 12.1 (90 trays), what were the calculated column height and total annualized cost?

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Question 35

In Example 12.1, why was the initial 40-tray design considered suboptimal?

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Question 36

Why is Discounted Cash Flow Rate of Return (DCFROR) described as an intrinsically difficult optimization objective?

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Question 37

What is a potential issue with using Net Present Value (NPV) as an optimization objective?

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Question 38

When optimizing a single variable that is bounded by constraints, what must be checked in addition to stationary points?

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Question 39

What property defines a convex feasible region in multivariable optimization?

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Question 40

Which class of methods can be used to overcome the problem of an optimization algorithm converging to a local optimum?

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Question 41

In which two industrial areas are operations research methods like LP and MILP widely used?

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Question 42

For batch and semicontinuous processes that have nonproductive periods, what is typically optimized to find the minimum cost per unit of production?

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Question 43

Which of the following is listed as one of the most important things for a design engineer to understand when performing industrial process design optimization?

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Question 44

What is a key difference in the number of new points calculated per cycle between a regular three-point interval search and a golden-section search?

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Question 45

In the 90-tray design for the distillation column in Example 12.1, what were the calculated reflux ratio and column diameter?

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Question 46

What was the approximate total annualized cost savings in Example 12.1 when moving from the initial 40-tray design to the improved 90-tray design?

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Question 47

What is the term for a problem where the feasible region defined by the constraints has no solution?

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Question 48

Why must the boundaries of the search space be checked when optimizing a single-variable function?

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Question 49

Which optimization method involves approximating the objective function as a quadratic function and is well-suited for highly nonlinear problems with relatively few variables?

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Question 50

What type of optimization problem results when discrete variables are introduced into a nonlinear program (NLP)?

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