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S14- Bus 104 > Midterm 1 > Flashcards

Midterm 1 Flashcards

1
Q

Problem solving procedure

A

Structure the Problem

  1. Define the problem
  2. Identify the problem
  3. Determine the criteria

Analyzing the Problem

  1. Evaluate the alternatives
  2. Choose an alternative

Implementation and testing

  1. Implement the alternative
  2. Evaluate the results
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2
Q

Single-criterion decision problems

A

Problems in which the objective is to find the best solution with respect to one criterion

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3
Q

Multicriteria decision problems

A

Problems that involve more than one criterion

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4
Q

Qualitative Analysis

A

Based largely on the manager’s judgement and experience
Includes the manager’s intuition
Is more of an art than a science

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5
Q

Quantitative Analysis

A

Focus on the quantitative facts or data associated with the problem
Develop mathematical expressions that describe the objectives, the constraints, and other relationships that exist in the problem
Use 1+ quantitative methods to make a recommendation

Use when problem is:
Complex
Important
New
Repetitive
Steps:
Model Development
Data Preparation
Model Solution
Model Testing and Validation
Report Generation
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6
Q

Models

A

Simplified version of what it represents
Valid if accurately represents the relevant characteristics of the object or decision being studied

Involve less risk, less time, less expenses, feasible

Give insight and understanding that improve decision making

Steps:
Define decision variables
Objective function (e.g., max. 10X)
Constraints (e.g., 5X <= 40)
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7
Q

Uncontrollable Inputs

A

Environmental factors that are not under the control of the decision maker
E.g., given: production time per unit (5 hours)

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8
Q

Decision Variables

A

Controllable inputs

Decision alternatives specified by the decision maker

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9
Q

Data Preparation

A

Data required by the model: values of uncontrollable inputs

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10
Q

Optimal solution

A

The BEST output

Is a feasible solution

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11
Q

Infeasible solution

A

Does NOT satisfy all the constraints

Is REJECTED

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12
Q

Feasible solution

A

Satisfies all of the model constraints

Is a candidate for optimal solution

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13
Q

Model Testing and Validation

A

Often, accuracy cannot be assessed until solutions are generated
-> generate small that have known (or at least expected) solutions

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14
Q

Report Generation

A

Based on the results of the model
Should be easily understood

Include:

  • recommended solution/decision
  • other pertinent info about the results
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15
Q

Fixed cost

A

Cost that is incurred independent of the quality sold/produced

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16
Q

Unit variable cost

A

Cost of producing one unit

17
Q

Marginal cost

A

Cost of producing one ADDITIONAL unit

18
Q

Marginal revenue

A

Income from selling one ADDITIONAL unit

19
Q

Variable cost (equation)

A

(number of units produced) * (unit variable cost)

20
Q

Total cost (equation)

A

fixed cost * variable cost

21
Q

Revenue (equation)

A

sales price * number of units sold

22
Q

Profit (equation)

A

revenue - total cost

23
Q

Break even

A

Profit (revenue - total cost) is zero

24
Q

Linear programming

A

Problem solving approach developed for situations involving max or mini a linear function subject to linear constraints that limit the degree to which the object can be pursued

Must be a linear function
Must be =, or =

If more than two variables, graphical solution model

25
Q

Integer linear programming

A

Used for problems that can be set up as linear programs with the additional requirement that some or all of them decision recommendations be integer values

26
Q

Network models

A

Specialized solution procedures for problems in transportation system design, information system design, project scheduling, etc.

27
Q

Simulation

A

Technique used to model the operation of a system. This technique employs a computer program to model the operation and perform simulation computations

28
Q

Inventory models

A

Used by managers faced with the problems of maintaining sufficient inventories to meet demand for goods and, at the same time, incurring the lowest possible inventory holding costs

29
Q

Waiting line (or queuing) models

A

Help managers understand and make better decisions concerning the operation of systems involving waiting lines

30
Q

Project scheduling (PERT and CPM)

A

help managers in planning, scheduling, and controlling projects that consist of numerous separate jobs or tasks performed by a variety of departments, individuals, and so forth

31
Q

Decision analysis

A

can be used to determine optimal strategies in situations involving several decision alternatives and uncertainty of future events

32
Q

Problem formulation or modeling

A

Process of translating a verbal statement of a problem into a mathematical statement

33
Q

Summary of graphical solution procedure for maximization of problems

A
  1. Prepare a graph of the feasible solutions for each of the constraints
  2. Determine the feasible region that satisfies all the constrains simultaneously
  3. Draw an objective function line
  4. Move parallel objective function lines toward larger objective function values w/o entirely leaving the feasible region
  5. Any feasible solution on the objective function line with the largest possible value is an optimal solution

Optimal solution to a LP problem can be found at an extreme point of the feasible region

34
Q

Slack variable

A

<=
Add to problem
RHS - LHS

35
Q

Surplus variable

A

> =
Subtract from problem
LHS - RHS

36
Q

Binding constraints

A

Intersection gives optimal point and slack/surplus variables equal zero

37
Q

Spreadsheet: for objective function value

A

Multiply Final Value and Objective Coefficient

38
Q

Spreadsheet: reduced cost

A

When increase value of X1

objective coefficient by reduced cost

39
Q

Summary of graphical solution procedures from MINIMIZATION problems

A
  1. Prepare a graph of the feasible solutions for each of the constraints
  2. Determine the feasible region that satisfies all the constrains simultaneously
  3. Draw an objective function line
  4. Move parallel objective function lines toward SMALLER objective function values w/o entirely leaving the feasible region
  5. Any feasible solution on the objective function line with the SMALLEST possible value is an optimal solution

S14- Bus 104 (1 decks)

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