Solution Manual for An Introduction to Management Science 15th Edition by Anderson

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By: Anderson

Edition: 15th Edition

Resource Type: Solution manual

Solution Manual for An Introduction to Management Science 15th Edition by Anderson

Chapter 1

Introduction

Learning Objectives

1. Develop a general understanding of the management science/operations research approach to decision making.

1. Realize that quantitative applications begin with a problem situation.

1. Obtain a brief introduction to quantitative techniques and their frequency of use in practice.

1. Understand that managerial problem situations have both quantitative and qualitative considerations that are important in the decision making process.

1. Learn about models in terms of what they are and why they are useful (the emphasis is on mathematical models).

1. Identify the step-by-step procedure that is used in most quantitative approaches to decision making.

1. Learn about basic models of cost, revenue, and profit and be able to compute the breakeven point.

1. Obtain an introduction to the use of computer software packages such as Microsoft Excel in applying quantitative methods to decision making.

1. Understand the following terms:

model                                                     infeasible solution

objective function                               management science

constraint                                             operations research

deterministic model                             fixed cost

stochastic model                                 variable cost

feasible solution                                  breakeven point

Solutions:

1. Management science and operations research, terms used almost interchangeably, are broad disciplines that employ scientific methodology in managerial decision making or problem solving. Drawing upon a variety of disciplines (behavioral, mathematical, etc.), management science and operations research combine quantitative and qualitative considerations in order to establish policies and decisions that are in the best interest of the organization.

1. Define the problem

Identify the alternatives

Determine the criteria

Evaluate the alternatives

Choose an alternative

For further discussion see section 1.3

1. See section 1.2.

1. A quantitative approach should be considered because the problem is large, complex, important, new and repetitive.

1. Models usually have time, cost, and risk advantages over experimenting with actual situations.

1. Model (a) may be quicker to formulate, easier to solve, and/or more easily understood.

1. Let d = distance

m = miles per gallon

c = cost per gallon,

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Solution Manual for An Introduction to Management Science 15th Edition by Anderson

Chapter 1 Introduction    Learning Objectives
1. Develop a general understanding of the management science/operations research approach to decision making.

1. Realize that quantitative applications begin with a problem situation.

1. Obtain a brief introduction to quantitative techniques and their frequency of use in practice.

1. Understand that managerial problem situations have both quantitative and qualitative considerations that are important in the decision making process.

1. Learn about models in terms of what they are and why they are useful (the emphasis is on mathematical models).

1. Identify the step-by-step procedure that is used in most quantitative approaches to decision making.

1. Learn about basic models of cost, revenue, and profit and be able to compute the breakeven point.

1. Obtain an introduction to the use of computer software packages such as Microsoft Excel in applying quantitative methods to decision making.

1. Understand the following terms:
model                                                     infeasible solution objective function                               management science constraint                                             operations research deterministic model                             fixed cost stochastic model                                 variable cost feasible solution                                  breakeven point   Solutions:
1. Management science and operations research, terms used almost interchangeably, are broad disciplines that employ scientific methodology in managerial decision making or problem solving. Drawing upon a variety of disciplines (behavioral, mathematical, etc.), management science and operations research combine quantitative and qualitative considerations in order to establish policies and decisions that are in the best interest of the organization.

1. Define the problem
Identify the alternatives   Determine the criteria   Evaluate the alternatives   Choose an alternative   For further discussion see section 1.3
1. See section 1.2.

1. A quantitative approach should be considered because the problem is large, complex, important, new and repetitive.

1. Models usually have time, cost, and risk advantages over experimenting with actual situations.

1. Model (a) may be quicker to formulate, easier to solve, and/or more easily understood.

1. Let d = distance
m = miles per gallon c = cost per gallon,

Solution Manual for Operations Management 13th Edition by Stevenson

chapter 19 Linear Programming Teaching Notes The main goal of this supplement is to provide students with an overview of the types of problems that have been solved using linear programming (LP). In the process of learning the different types of problems that can be solved with LP, students also must develop a very basic understanding of the assumptions and special features of LP problems of management test bank. Students also should learn the basics of developing and formulating linear programming models for simple problems, solve two-variable linear programming problems by the graphical procedure, and interpret the resulting outcome. In the process of solving these graphical problems, we must stress the role and importance of extreme points in obtaining an optimal solution. Improvements in computer hardware and software technology and the popularity of the software package Microsoft Excel make the use of computers in solving linear programming problems accessible to many users. Therefore, a main goal of the chapter should be to allow students to solve linear programming problems using Excel. More importantly, we need to ensure that students are able to interpret the results obtained from Excel or any another computer software package. Answers to Discussion and Review Questions
1. Linear programming is well-suited to constrained optimization problems that satisfy the following assumptions:
2. Linearity: The impact of decision variables is linear in constraints and the objective function.
3. Divisibility: Noninteger values of decision variables are acceptable.
4. Certainty: Values of parameters are known and constant.
5. Nonnegativity: Negative values of decision variables are unacceptable.
6. The “area of feasibility,” or feasible solution space is the set of all combinations of values of the decision variables that satisfy all constraints. Hence, this area is determined by the constraints.
7. Redundant constraints do not affect the feasible region for a linear programming problem. Therefore, they can be dropped from a linear programming problem without affecting the feasible solution space or the optimal solution.
8. An iso-cost line represents the set of all possible combinations of two input decision variables that result in a given cost. Likewise, an iso-profit line represents all of the possible combinations of two output variables that results in a given profit.
9. Sliding an objective function line towards the origin represents a decrease in its value (i.e., lower cost, profit, etc.). Sliding an objective function line away from the origin represents an increase in its value.
10. a. Basic variable: In a linear programming solution, it is a variable not equal to zero.
11. Shadow price: It is the change in the value of the objective function for a one-unit change in the right-hand-side value of a constraint.
12. Range of feasibility: The range of values for the right-hand-side value of a constraint over which the shadow price remains the same.
13. Range of optimality: The range of values over which the solution quantities of all the decision variables remain the same.
Solution to Problems
1. a. Graph the constraints and the objective function:
Material constraint: 6x1 4x2 ≤ 48 Replace the inequality sign with an equal sign: 6x1 4x2 = 48 Set x1 = 0 and solve for x2: 6(0) 4x2 = 48 4x2 = 48 x2 = 12 One point on the line is (0, 12). Set x2 = 0 and solve for x1: 6x1 4(0) = 48 6x1 = 48 x1 = 8 A second point on the line is (8,0).   Labor constraint: 4x1 8x2 ≤ 80 Replace the inequality sign with an equal sign: 4x1 8x2 = 80 Set x1 = 0 and solve for x2: 4(0) 8x2 = 80 8x2 = 80 x2 = 10 One point on the line is (0, 10). Set x2 = 0 and solve for x1: 4x1 8(0) = 80 4x1 = 80 x1 = 20 A second point on the line is (20, 0).   Objective function: Let 4x1 3x2 = 24. Set x1 = 0 and solve for x2: 4(0) 3x2 = 24 3x2 = 24 x2 = 8 One point on the line is (0, 8). Set x2 = 0 and solve for x1: 4x1 3(0) = 24 4x1 = 24 x1 = 6 A second point on the line is (6, 0).   The graph and the feasible solution space (shaded) are shown below:

Solution Manual for Operations Management 6th CANADIAN Edition by Stevenson

Chapter No 1 INTRODUCTION TO Operations Management Teaching Notes The initial meeting with the class (the first chapter) is primarily to overview the course (and textbook), and to introduce the instructor and his/her interest in Operations Management (OM). The course outline (syllabus), the objectives of the course and topics, chapters, and pages of text covered in the course, as well as problems/mini-cases, to be done in class, videos to watch, Excel worksheets to use, etc. are announced to the class. Many students may know little about OM and the types of jobs available. This point can be addressed in order to generate enthusiasm for the course. The Learning Objectives at the beginning of the chapter indicate the highlights of the chapter. Answers to Discussion and Review Questions
1. Operations management is the management of processes (i.e., the sequence of activities and resources)that create goods and/or provide services.

1. Production/operations planner/scheduler/controller, demand planner (forecaster), quality specialist, logistics coordinator, purchasing agent/buyer, supply chain manager, materials planner, inventory clerk/manager, production/operations manager.

1. a.       Because a large % of a company’s expenses occur in the operations, e.g., purchasing materials and workforce salaries, more efficient operations can result in large increases in profits.
2. A number of management jobs are in OM.
3. Activities in all other areas of any organization are all interrelated with OM.
4. Operations innovations lead to the marketplace and strategic benefits.
5. The three major functions of organizations are operations, finance, and marketing. Operations is concerned with the creation of goods and services identified by marketing, finance is concerned with the provision of funds necessary for operations and investment of extra funds, and marketing is concerned with promoting and/or selling goods or services.
6. The operations function consists of all activities that are directly related to producing goods or providing services. It adds value during the transformation process (the difference between the cost of inputs and the price of outputs). An operations manager manages the transformation function.                                                             He/she is responsible for planning and using the resources (labor, machines, and materials). The kind of work that operations managers do varies from organization to organization (largely because of the different goods or services involved). For example, a store/restaurant manager is in effect an operations manager. See Figure 1-6 for examples of typical activities performed by operations managers.
7. Design decisions are usually strategic and long term (1–5 years or so ahead), whereas planning and control decisions are shorter term. In particular, planning decisions are tactical and medium-term (1–12 months or so ahead), and control decisions (including scheduling and execution) are short term (1–12 weeks or so ahead). Design involves decisions that relate to goods and service design, capacity, acquisition of equipment, the arrangement of departments, and location of facilities.Planning/control activities involve management of personnel, quality control/assurance, inventory planning and control, production planning, and scheduling.

Solution Manual for Principles of Supply Chain Management 5th Edition by Wisner

PRINCIPLES OF SUPPLY CHAIN MANAGEMENT: A BALANCED APPROACH, 5thEd. Answers to Questions/Problems Chapter One

Discussion Questions

1. Define the term supply chain management in your own words, and list its most important activities.
Ans.: The Supply-Chain Council’s definition of supply chain management is“[m]anaging supply and demand, sourcing raw materials and parts, manufacturing and assembly, warehousing and inventory tracking, order entry and order management, distribution across all channels, and delivery to the customer. These are also the most important activities, however integration of key supply chain processes might also be included in there.
1. Can a small business like a local sandwich or bicycle shop benefit from practicing supply chain management?What would they most likely concentrate on?
Ans.: Yes, any organization can implement at least some of the important concepts. A good place to start is the rationalization or reduction of the supply base. Small businesses might also want to concentrate on customers as a starting point.
1. Describe and draw a supply chain for a bicycle repair shop and list the important supply chain members.
Ans.: This will vary from student to student, but should include for instance parts suppliers, bicycle suppliers and other suppliers (ie, helmet suppliers) and services (ie, repair services) as 1st-tier suppliers and bicycle owners as 1st-tier customers.
1. Can a bicycle repair shop have more than one supply chain? Explain.
Ans.: Yes. Every repair item the firm stocks has potentially a different supply chain associated with it.
1. What roles do “collaboration” and “trust” play in the practice of supply chain management?
Ans.: This is essential for process integration. Sharing information and determining joint strategies is part of the integration/collaboration process, and to do this, trust must be present between the customer/focal firm/supplier.
1. Why don’t firms just become more vertically integrated (eg. buy out suppliers and customers), instead of trying to manage their supply chains?
Ans.: This could cause a loss of focus and keep managers/employees from doing their core competencies, resulting in loss of performance.
1. What types of organizations would benefit the most from practicing supply chain management? What sorts of improvements could be expected?
Ans.: Firms with many suppliers, many complex products, large inventories and many customers (in other words, firms with many supply chains). Gains would be lower purchasing costs, lower carrying costs, better product quality, and better customer service.
1. What are the benefits of supply chain management?
Ans.: Reduction of the bullwhip effect, better buyer/supplier relationships, better quality, lower costs, better customer service, higher demand, more profits.
1. Can nonprofit, educational, or government organizations benefit from supply chain management? How?
Ans.: Yes. All services and organizations can benefit in terms of at least better customer service, better inventory management, and cheaper purchase prices.

Solution Manual for Practical Management Science 6th Edition by Winston

Table of Contents 1. Introduction to Modeling. 2. Introduction to Spreadsheet Modeling. 3. Introduction to Optimization Modeling. 4. Linear Programming Models. 5. Network Models. 6. Optimization Models with Integer Variables. 7. Nonlinear Optimization Models. 8. Evolutionary Solver: An Alternative Optimization Procedure. 9. Decision Making Under Uncertainty. 10. Introduction to Simulation Modeling. 11. Simulation Models. 12. Queueing Models. 13. Regression and Forecasting Models. 14. Data Mining 15. Project Management 16. Multiobjective Decision Making 17. Inventory and Supply Chain Models

Chapter 1

1.2 Statistics for Management and Economics  Descriptive techniques summarize data. Inferential techniques draw inferences about a population based on sample data. 1.3 Statistics for Management and Economics  a The population is the 25,000 registered voters. b The sample is the 200 registered voters. cThe 48% figure is the statistic   1.4 Statistics for Management and Economics  a The population is the complete production run. b The sample is comprised of the 1,000 chips. c The parameter is the proportion of defective chips in the production run. d The statistic is the proportion of defective chips in the sample. e The 10% figure refers to the parameter. fThe 7.5% figure refers to the statistic. g We can estimate the population proportion is 7.5%. Statistical inference methods will allow us to determine whether we have enough statistical evidence to reject the claim.as the sample proportion.   1.5 Statistics for Management and Economics  Draw a random sample from the population of graduates who have majored in your subject and a random sample of graduates of other majors and record their highest salary offers.   1.6 Statistics for Management and Economics  a Flip the coin (say 100 times) and record the number of heads (assuming that you are interested in the number of heads). b The population is composed of the theoretical result of flipping the coin an infinite number of times and recording either “heads” or “tails”. cThe sample is comprised of the “heads” and “tails” in the sample. d The parameter is the proportion of heads (again assuming that your interest is the number of heads rather than tails) in the population. e The statistic is the proportion of heads (or tails depending on the choice made in part d). fThe sample statistic can be used to judge whether the coin is actually fair.   1.7 a We would conclude that the coin is not fair. b We may conclude that there is some evidence that the coin is not fair.   1.8 aThe population is made up of the propane mileage of all the cars in the fleet. b The parameter is the mean propane mileage of all the cars in the fleet. c The sample is composed of the propane mileage of the 50 cars. d The statistic is the mean propane mileage of the 50 cars in the sample. e We can use the sample statistic to estimate the population parameter.
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