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Questions and Answers
What term encompasses the knowledge involving quantitative approaches to decision making?
What term encompasses the knowledge involving quantitative approaches to decision making?
Which step is NOT part of the problem-solving process?
Which step is NOT part of the problem-solving process?
Which of the following is one of the first five steps of the problem-solving process?
Which of the following is one of the first five steps of the problem-solving process?
Which development has significantly contributed to the growth of management science in business?
Which development has significantly contributed to the growth of management science in business?
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What does the term 'breakeven point' specifically refer to in the context of management science?
What does the term 'breakeven point' specifically refer to in the context of management science?
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Which of the following best describes operations research?
Which of the following best describes operations research?
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Which role do qualitative approaches play in managerial decision making?
Which role do qualitative approaches play in managerial decision making?
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What is the main goal of management science techniques?
What is the main goal of management science techniques?
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What type of model physically resembles the object it represents?
What type of model physically resembles the object it represents?
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Which of the following is NOT considered an advantage of using models over real situations?
Which of the following is NOT considered an advantage of using models over real situations?
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In the mathematical model for the production problem, what does the variable x represent?
In the mathematical model for the production problem, what does the variable x represent?
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What is the objective function in the mathematical model of the production problem?
What is the objective function in the mathematical model of the production problem?
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Which constraint represents the maximum hours available for production in the simple production problem?
Which constraint represents the maximum hours available for production in the simple production problem?
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What kind of inputs are the profit per unit and production time in the mathematical model?
What kind of inputs are the profit per unit and production time in the mathematical model?
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How are mathematical models primarily used in relation to real situations?
How are mathematical models primarily used in relation to real situations?
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What is the marginal cost of producing one additional unit?
What is the marginal cost of producing one additional unit?
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What type of cost does the $3,000 incurred during a changeover represent?
What type of cost does the $3,000 incurred during a changeover represent?
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How much total revenue will be generated from the sale of x units of Viper covers?
How much total revenue will be generated from the sale of x units of Viper covers?
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What must production and sales exceed to achieve a profit?
What must production and sales exceed to achieve a profit?
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What is the marginal revenue from selling one additional unit of Viper covers?
What is the marginal revenue from selling one additional unit of Viper covers?
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What equation would represent the condition for breakeven?
What equation would represent the condition for breakeven?
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What is the total profit represented by?
What is the total profit represented by?
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In terms of production volume, how does the marginal cost affect total cost?
In terms of production volume, how does the marginal cost affect total cost?
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What term is used to describe problems that focus on finding the best solution with respect to a single criterion?
What term is used to describe problems that focus on finding the best solution with respect to a single criterion?
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Which of the following describes quantitative analysis in the decision-making process?
Which of the following describes quantitative analysis in the decision-making process?
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What is the primary purpose of model testing and validation?
What is the primary purpose of model testing and validation?
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Which of the following is NOT a typical objective function in business and economics?
Which of the following is NOT a typical objective function in business and economics?
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What is the primary reason for adopting a quantitative analysis approach in decision-making?
What is the primary reason for adopting a quantitative analysis approach in decision-making?
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Which three steps of the decision-making process are combined under 'Structuring the Problem'?
Which three steps of the decision-making process are combined under 'Structuring the Problem'?
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What is essential for a managerial report generated from a model?
What is essential for a managerial report generated from a model?
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How is qualitative analysis primarily characterized in decision-making?
How is qualitative analysis primarily characterized in decision-making?
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How should inaccuracies in a model be addressed?
How should inaccuracies in a model be addressed?
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In the context of the cost-volume model, what does 'x' represent?
In the context of the cost-volume model, what does 'x' represent?
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Which of the following is NOT a characteristic of multicriteria decision problems?
Which of the following is NOT a characteristic of multicriteria decision problems?
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What type of problems should be used for model testing?
What type of problems should be used for model testing?
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What is the significance of the term 'model development' in the quantitative analysis process?
What is the significance of the term 'model development' in the quantitative analysis process?
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Which of the following is a common decision variable in business models?
Which of the following is a common decision variable in business models?
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What does the flowchart for the decision-making process suggest about the organization of problem-solving steps?
What does the flowchart for the decision-making process suggest about the organization of problem-solving steps?
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What should be included in a managerial report aside from the recommended decision?
What should be included in a managerial report aside from the recommended decision?
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What is the primary goal of linear programming?
What is the primary goal of linear programming?
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Which management science technique involves making decisions based on integer values?
Which management science technique involves making decisions based on integer values?
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What purpose do distribution and network models serve?
What purpose do distribution and network models serve?
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What does the analytic hierarchy process allow managers to do?
What does the analytic hierarchy process allow managers to do?
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What is goal programming used for?
What is goal programming used for?
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What is the main function of waiting line (or queuing) models?
What is the main function of waiting line (or queuing) models?
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Which method is primarily utilized for predicting future aspects of a business operation?
Which method is primarily utilized for predicting future aspects of a business operation?
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What technique allows for planning, scheduling, and controlling project tasks?
What technique allows for planning, scheduling, and controlling project tasks?
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Study Notes
Introduction to Management Science
- Management science is a body of knowledge focused on quantitative approaches to decision-making.
- It includes decision science and operations research.
- It has roots in World War II and is used extensively in businesses and industries.
- Key factors driving its success include methodological developments, particularly in linear programming (e.g., simplex method), and the explosion of computing power.
Chapter 1 - Introduction
- Chapter Objectives: Define management science, operations research, and decision science. List steps in decision-making, describing both qualitative and quantitative approaches. Explain the modeling process. Formulate basic models for cost, revenue, and profit to calculate the breakeven point.
- Chapter Contents: The chapter covers Problem Solving and Decision Making, Quantitative Analysis and Decision Making, Models of Cost, Revenue, and Profit, and Management Science Techniques.
1-1 Problem Solving
- Problem solving is the process of identifying a difference between the actual and desired state and then taking action to resolve it.
- Seven steps:
- Define the problem
- Determine alternative solutions
- Determine criteria for evaluating solutions
- Evaluate alternatives
- Choose an alternative (make a decision)
- Implement the selected alternative
- Evaluate the results
1-1 Decision-Making Process
- Decision-making refers to the first five steps of the problem-solving process.
- Single-criterion problems: focus on finding the best solution based on a single criterion.
- Multi-criteria problems: involve more than one criterion.
- Decision is the choice of the best alternative.
1-2 Quantitative Analysis and Decision Making
- Decision-making process: A flowchart for structuring and analyzing the problem combines the first three steps (defining the problem, identifying alternatives, determining criteria) under "Structuring the problem" and the last two steps (evaluating alternative and choosing an alternative) under "Analyzing the problem".
- Qualitative analysis: Based largely on the manager's judgment and experience. Includes intuitive "feel" for the problem. More of an art than science.
- Quantitative analysis: Based on the quantitative facts or data associated with the problem. Uses mathematical expressions to describe objectives, constraints, and other relationships in the problem. One or more quantitative methods may be used to make a recommendation.
1-3 Quantitative Analysis
- Reasons for using quantitative analysis:
- Complex problems
- Very important problems
- New problems
- Repetitive problems
- Four steps of quantitative analysis:
- Model development
- Data preparation
- Model solution
- Report generation
1-3 Step 1: Model Development
- A model is a representation of a real object or situation.
- Main model forms:
- Iconic models: physical replicas of real objects
- Analog models: do not physically resemble the object
- Mathematical models: use expressions/formulas with assumptions and statistical analyses
- Models can save time, reduce cost, and reduce risk when compared with experimenting with the real situation.
1-3 Example: Simple Production Problem
- A mathematical model has an objective function with controllable inputs (decision variables), and constraints influenced by uncontrollable inputs (environmental factors).
- An example problem seeks the optimal production volume maximizing profit.
1-3 A Mathematical Model
- Decision variable: number of units produced.
- Objective function: with 10$ profit per unit is 10*x.
- Uncontrollable Inputs: Example; profit per unit ($10) & production time per unit(5 hours).
- Constraints: The production capacity is 40 hours/week - Example ; 5x ≤ 40.
1-3 Types of Mathematical Models
- Deterministic models: all inputs known and unchangeable.
- Stochastic models: one or more inputs are uncertain & variable.
1-3 Step 2: Data Preparation
- Data preparation must specify all uncontrollable inputs before analysis.
- Prepare enough data to form the mathematical model- data preparation can be complex with many errors.
1-3 Step 3: Model Solution
- Trial-and-error process to find an optimal solution for a mathematical model.
- Identify decision variable values yielding the best output, the optimal solution.
- Infeasible alternatives may not satisfy all constraints.
1-3 A Flow Chart of Simple Production Model
- Summarizes all input and how the model works.
1-3 After the Solution
- Model validation: use small known issues as a test for the larger problem
- Report generation: report should be easy to understand, the report should include recommended decision and other relevant information (Example: sensitivity of model to assumptions/data).
1-4 Models of Cost, Revenue, and Profit
- Quantitative models relating decision variables (e.g., production or sales volume) to objective functions (e.g., cost, revenue, profit).
1-4 Cost-Volume Models
- Example given to find the total cost of producing a certain number of units (e.g. total cost of producing a volume of x units of the Viper).
- The marginal cost = the increase in cost associated with producing one more unit.
1-4 Revenue and Profit-Cost Models
- Models relating revenue (and associated profit) to the volume of goods sold, considering the total revenue from selling x units.
1-4 breakeven analysis
- Total revenue equals total costs, point where there is no profit, nor loss
- Finding a breakeven point involves setting the total profit = 0 & solving for x (volume).
1-5 (Most Frequent) Management Science Techniques
- Linear programming: Maximizing/minimizing a linear function subject to linear constraints.
- Integer linear programming: Linear programming with integer requirement constraints.
- Distribution & network models: Specialized solutions for transportation, network, information systems, and project scheduling problems.
- Simulation: computer programs for simulation computations modeling a system's operation.
1-5 (Other) Management Science Techniques
- Nonlinear programming: Maximizing/minimizing a nonlinear function with nonlinear constraints.
- Inventory models: Maintaining required inventory while minimizing inventory costs.
- Waiting line models: Assessing and improving decision-making of waiting lines/queues.
- Forecasting methods: Prediction of future aspects.
- Goal programming: Solving multi-criteria decision problems within linear programming frameworks.
- Analytic hierarchy process, PERT & CPM: Aids in planning tasks.
- Decision analysis: Determines optimal strategies in the presence of multiple alternatives & uncertain future outcomes.
- Markov-process models: Analyzing how systems evolve over repeated trials.
Summary
- Management science helps managers make better decisions by providing quantitative tools for analyzing and resolving real-world business problems.
- Mathematical models represent real-world situations with key aspects but are not perfect representations.
- Management science aims to find the "best" or optimal solution for a problem.
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Description
Explore the fundamental concepts of management science in this quiz based on Chapter 1. Learn about operations research, decision-making processes, and various models used in quantitative analysis. Understand how these principles apply to real-world business scenarios, including cost, revenue, and profit calculations.
