Introduction to Operations Research (11th Edition, 2020 – Hillier & Lieberman) | Complete Solutions Manual PDF

ALL CHAPTERS COVERED

, TABLE OF CONTENTS

SOLUTIONS TO END-OF-CHAPTER PROBLEMS AND CASES

CHAPTER 1 Introduction 1-1
CHAPTER 2 Overview of the Operations Research Modeling Approach 2-1
CHAPTER 3 Introduction to Linear Programming 3-1
CHAPTER 4 Solving Linear Programming Problems: The Simplex Method 4-1
CHAPTER 5 The Theory of the Simplex Method 5-1
CHAPTER 6 Duality Theory and Sensitivity Analysis 6-1
CHAPTER 7 Other Algorithms for Linear Programming 7-1
Supplement to Chapter 7 7S-1
CHAPTER 8 The Transportation and Assignment Problems 8-1
CHAPTER 9 Network Optimization Models 9-1
CHAPTER 10 Dynamic Programming 10-1
CHAPTER 11 Integer Programming 11-1
CHAPTER 12 Nonlinear Programming 12-1
CHAPTER 13 Metaheuristics 13-1
CHAPTER 14 Game Theory 14-1
CHAPTER 15 Decision Analysis 15-1
CHAPTER 16 Markov Chains 16-1
CHAPTER 17 Queueing Theory 17-1
CHAPTER 18 Inventory Theory 18-1
Supplement 1 to Chapter 18 18S1-1
Supplement 2 to Chapter 18 18S2-1
CHAPTER 19 Markov Decision Processes 19-1
CHAPTER 20 Simulation 20-1
Supplement 1 to Chapter 20 20S1-1
Supplement 2 to Chapter 20 20S2-1
Supplement 3 to Chapter 20 20S3-1
CHAPTER 21 The Art of Modeling with Spreadsheets 21-1
CHAPTER 22 Project Management with PERT/CPM 22-1
CHAPTER 23 Additional Special Types of Linear Programming Problems 23-1
CHAPTER 24 Probability Theory 24-1
CHAPTER 25 Reliability 25-1
CHAPTER 26 The Application of Queueing Theory 26-1
CHAPTER 27 Forecasting 27-1
CHAPTER 28 Examples of Performing Simulations on Spreadsheets with Crystal Ball 28-1

, CHAPTER 1: INTRODUCTION


1.3-1.
Answers will vary.
1.3-2.
Answers will vary.
1.3-3.
By using operations research (OR), FedEx managed to survive crises that could drive it
out of business. The new planning system provided more flexibility in choosing the
destinations that it serves, the routes and the schedules. Improved schedules yielded into
faster and more reliable service. OR applied to this complex system with a lot of
interdependencies resulted in an efficient use of the assets. With the new system, FedEx
maintained a high load factor while being able to service in a reliable, flexible and
profitable manner. The model also enabled the company to foresee future risks and to
take measures against undesirable outcomes. The systematic approach has been effective
in convincing investors and employees about the benefits of the changes. Consequently,
"today FedEx is one of the nation's largest integrated, multi-conveyance freight carriers"
[p. 32].




1-1

, CHAPTER 2: OVERVIEW OF THE OPERATIONS RESEARCH
MODELING APPROACH

2.1-1.
(a) The rise of electronic brokerage firms in the late 90s was a threat against full-service
financial service firms like Merrill Lynch. Electronic trading offered very low costs,
which were hard to compete with for full-service firms. With banks, discount brokers and
electronic trading firms involved, the competition was fierce. Merrill Lynch needed an
urgent response to these changes in order to survive.
(b) "The group's mission is to aid strategic decision making in complex business
situations through quantitative modeling and analysis" [p.8].
(c) The data obtained for each client consisted of "data for six categories of revenue, four
categories of account type, nine asset allocation categories, along with data on number of
trades, mutual fund exchanges and redemptions, sales of zero coupon bonds, and
purchases of new issues" [p. 10].
(d) As a result of this study, two main pricing options, viz., an asset-based pricing option
and a direct online pricing option were offered to the clients. The first targeted the clients
who want advice from a financial advisor. The clients who would choose this option
would be charged at a fixed rate of the value of their assets and would not pay for each
trade. The latter pricing option was for the clients who want to invest online and who do
not want advice. These self-directed investors would be charged for every trade.
(e) "The benefits were significant and fell into four areas: seizing the marketplace
initiative, finding the pricing sweet spot, improving financial performance, and adopting
the approach in other strategic initiatives" [p.15].
2.1-2.
(a) This study arose from GM's efforts to survive the competition of the late 80s. Various
factors, including the rise of foreign imports, the increase in customer expectations and
the pricing constraints, forced GM to close plants and to incur large financial losses.
While trying to copy Japanese production methods directly, GM was suffering from
"missing production targets, working unscheduled overtime, experiencing high scrap
costs, and executing throughput-improvement initiatives with disappointing results" [p.
7]. The real problems were not understood and the company was continuously losing
money while the managers kept disagreeing about solutions.
(b) The goal of this study was "to improve the throughput performance of existing and
new manufacturing systems through coordinated efforts in three areas: modeling and
algorithms, data collection, and throughput-improvement processes" [p. 7].
(c) The data collection was automated by using programmable logic controllers (PLCs).
The software kept track of the production events including "machine faults and blocking
and starving events" [p. 13] and recorded their duration. The summary of this data was
then transferred to a centralized database, which converted this to workstation-
performance characteristics and used in validating the models, determining the bottleneck
processes and enhancing throughput.
(d) The improved production throughput resulted in more than $2.1 billion in
documented savings and increased revenue.
2-1