An Introduction to Management Science, 16/e (AE-Paperback)

本書序言

●FULL-COLOR INTERNAL DESIGN APPEALS TO STUDENTS AND HELPS CLARIFY KEY POINTS. Learning objectives now added to the beginning of each chapter map to specific end-of-chapter problems for improved instructional design and outcomes tracking. In addition, most problems now have brief, inline descriptions added.
●NEW WEBASSIGN DIGITAL RESOURCES AND VIDEOS GUIDE LEARNING. The most recent edition of WebAssign courseware now offers new chapter overview videos and problem walk-through videos (called "Watch Its") as well as additional resources to improve the depth and breadth of assignments and offer help for students completing homework and quizzes. A new test bank is also available to check student comprehension.
●REVISIONS, GUIDED BY READER FEEDBACK, FURTHER IMPROVE CONCEPT EXPLANATIONS. Expanded discussions clarify key concepts. For instance, Chapter 7 clearly introduces the feasibility table to aid the construction of conditional and corequisite constraints. Chapter 8 expands discussion of sensitivity analysis for nonlinear optimization, and Chapter 10 clarifies the when-to-order decision for the various inventory models. In addition, Chapter 11 offers revised technical notes on multiple-server queueing systems.
●NEW "MANAGEMENT SCIENCE IN ACTION" VIGNETTES AND PROBLEMS DEMONSTRATE CONCEPTS AT WORK. Six new "Management Science in Action" vignettes describe how material covered in this edition is actually used in practice today. In addition, more than 15 end-of-chapter problems are new and many are updated.

本書特色

●REAL DATA EXAMPLES DEMONSTRATE ACTUAL BUSINESS SITUATIONS AND CHALLENGES. Known for its practical, real-world emphasis, this book provides actual, timely data drawn from real business. Theses meaningful examples emphasize application as well as solid management science and quantitative methodology.
●PROVEN PROBLEM-SCENARIO APPROACH ENSURES COMPREHENSION. A hallmark strength of this text, the authors' unique problem-scenario approach introduces problems using the management science model and introduces each quantitative technique within an application setting. Students must apply the management science technique to each problem to generate a business solution or recommendation.
●CHAPTER CONTENT AND PROBLEMS ALIGN WITH LEARNING OBJECTIVES. Each chapter includes a list of learning objectives that reflects Bloom's taxonomy. Every end-of-chapter problem now includes a descriptive problem title and lists the learning objectives that correspond to the problem for convenient review.
●ROBUST ONLINE CONTENT REINFORCES AND EXPANDS UPON THE BOOK'S THOROUGH EXPLANATIONS. This edition's wealth of digital content provides Excel® templates that correspond with this edition's text examples, models and software.
●INTEGRATED SOFTWARE APPLICATIONS HELP STUDENTS MASTER CRITICAL SKILLS. The edition's hallmark approach integrates coverage of applications with Excel®, helping you equip students with critical problem-solving skills in Excel®.

本書序言

●全彩內部設計吸引學生並幫助澄清關鍵要點。每章的學習目標現在添加到章節開始的位置，以便與特定的章節結束問題相對應，以改善教學設計和結果追蹤。此外，大多數問題現在都有簡短的內嵌描述。

●新的WebAssign數位資源和視頻指導學習。最新版本的WebAssign課程軟體現在提供新的章節概述視頻和問題解說視頻（稱為“Watch Its”），以及其他資源，以提高作業的深度和廣度，並為學生完成作業和測驗提供幫助。還提供了一個新的測驗庫，以檢查學生的理解能力。

●根據讀者反饋進行的修訂進一步改進概念解釋。擴展的討論澄清了關鍵概念。例如，第7章清楚介紹了可行性表，以幫助構建條件和先決條件約束。第8章擴展了非線性優化的敏感性分析討論，第10章澄清了各種庫存模型的何時訂購決策。此外，第11章提供了關於多服務器排隊系統的修訂技術說明。

●新的“管理科學實踐”小品和問題展示了概念的應用。六個新的“管理科學實踐”小品描述了本版中涵蓋的材料如何在實踐中使用。此外，超過15個章節結束的問題是新的，其中許多已更新。

本書特色

●真實數據示例展示實際的商業情況和挑戰。以其實用的實際強調而聞名，本書提供了來自真實商業的實際及時數據。這些有意義的例子強調應用以及堅實的管理科學和量化方法。

●經過驗證的問題情境方法確保理解。本書的一個重要特點是作者獨特的問題情境方法，使用管理科學模型介紹問題，並在應用情境中介紹每種量化技術。學生必須將管理科學技術應用於每個問題，以生成商業解決方案或建議。

●章節內容和問題與學習目標相符。每章都包含一個反映布魯姆分類的學習目標列表。每個章節結束的問題現在都包含一個描述性問題標題，並列出與問題相對應的學習目標，以便方便回顧。

●豐富的線上內容強化並擴展了本書的詳細解釋。本版豐富的數位內容提供與本版文本示例、模型和軟體相對應的Excel®範本。

●整合的軟體應用幫助學生掌握關鍵技能。本版的特點方法將Excel®的應用與內容整合在一起，幫助您裝備學生在Excel®中具有關鍵的問題解決能力。

Jeffrey D. Camm is the Inmar Presidential Chair and senior associate dean of business analytics programs in the School of Business at Wake Forest University.
James J. Cochran is associate dean for research, a professor of applied statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama. 
Michael J. Fry is a professor of operations, business analytics and information systems as well as academic director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati.
Jeffrey W. Ohlmann is associate professor of business analytics and a Huneke Research Fellow in the Tippie College of Business at the University of Iowa.
David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati.
Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati.
Thomas A. Williams - Rochester Institude of Technology

Jeffrey D. Camm 是 Wake Forest University 商學院的 Inmar Presidential Chair 和高級副院長，負責業務分析項目。
James J. Cochran 是 The University of Alabama 的應用統計學教授，同時也是研究副院長和 Rogers-Spivey Faculty Fellow。
Michael J. Fry 是 University of Cincinnati Carl H. Lindner College of Business 的運營、業務分析和信息系統教授，同時也是 Center for Business Analytics 的學術主任。
Jeffrey W. Ohlmann 是 University of Iowa Tippie College of Business 的業務分析副教授和 Huneke Research Fellow。
David R. Anderson 是 University of Cincinnati 商學院的量化分析教授和名譽教授，同時也是知名作者。
Dennis J. Sweeney 是 University of Cincinnati 的量化分析名譽教授，同時也是 Center for Productivity Improvement 的創始人。
Thomas A. Williams 就讀於 Rochester Institude of Technology。

1. Introduction.
2. An Introduction to Linear Programming.
3. Linear Programming: Sensitivity Analysis and Interpretation of Solution.
4. Linear Programming Applications in Marketing, Finance, and Operations Management.
5. Advanced Linear Programming Applications.
6. Distribution and Network Models.
7. Integer Linear Programming.
8. Nonlinear Optimization Models.
9. Project Scheduling: PERT/CPM.
10. Inventory Models.
11. Waiting Line Models.
12. Simulation.
13. Decision Analysis.
14. Multicriteria Decisions.
15. Time Series Analysis and Forecasting.
16. Markov Processes.
Appendix A: Building Spreadsheet Models.
Appendix B: Areas for the Standard Normal Distribution.
Appendix C: Values of e–λ.
Appendix D: References and Bibliography.
Appendix E: Answers to Even-Numbered Exercises (MindTap Reader).

1. 簡介。
2. 線性規劃介紹。
3. 線性規劃：敏感度分析和解釋解答。
4. 線性規劃在市場營銷、金融和運營管理中的應用。
5. 高級線性規劃應用。
6. 分配和網絡模型。
7. 整數線性規劃。
8. 非線性優化模型。
9. 專案排程：PERT/CPM。
10. 存貨模型。
11. 排隊模型。
12. 模擬。
13. 決策分析。
14. 多準則決策。
15. 時間序列分析和預測。
16. 馬可夫過程。
附錄A：建立試算表模型。
附錄B：標準正態分佈的區域。
附錄C：e–λ的值。
附錄D：參考文獻和書目。
附錄E：偶數習題答案（MindTap Reader）。