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Applied Operational Research with SAS [Kõva köide]

(Department of Management and Marketing, University of Melbourne, Australia), (Professor and Chair in Business Analytics, Aston Business School, Aston University, Birmingham, UK)
  • Formaat: Hardback, 284 pages, kõrgus x laius: 234x156 mm, kaal: 640 g, 55 Tables, black and white; 151 Illustrations, black and white
  • Ilmumisaeg: 13-Dec-2011
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1439841306
  • ISBN-13: 9781439841303
Teised raamatud teemal:
Applied Operational Research with SASSuurem pilt
  • Formaat: Hardback, 284 pages, kõrgus x laius: 234x156 mm, kaal: 640 g, 55 Tables, black and white; 151 Illustrations, black and white
  • Ilmumisaeg: 13-Dec-2011
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1439841306
  • ISBN-13: 9781439841303
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781439841303.html
Märksõnad:
"Preface This book was written primarily for SAS users in operational research, or simply OR. We use a wide range of OR optimization problems to demonstrate how the SAS/OR procedures work. The problems include single criterion optimization problems (e.g., transportation, assignment, transshipment, minimum-cost capacitated flow, maximum flow, shortest path, assembly line balancing, and traveling salesman), project management decision problems (e.g., critical path analysis, and program evaluation and review technique), printed circuit board (PCB) assembly problems (e.g., PCB assembly line assignment, PCB component allocation, and PCB component sequencing for pick-and-place machines), and multiple-criteria decision-making problems (e.g., analytic hierarchy process, multiple-criteria logistics distribution, ordered weighted averaging, data envelopment analysis, and Malmquist productivity index). The emphasis in this book is to use PROC OPTMODEL, which is the most recent development in SAS for optimization problems. The principles of several other procedures are also presented. We believe that this is the first book to extensively and successfully cover the application of SAS/OR procedures to OR problems. In addition, this book was written for undergraduate and postgraduate students in OR and those who are interested in mathematical modeling techniques. We formulated the OR problems mentioned earlier as various types of mathematical models, including linear programming, integer linear programming, and goal-programming models. We also show the transformation of the minima- type formulation into a minimization-type formulation"--

"Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project management decisions, printed circuit board assembly, and multiple criteria decision making.The text begins with the algorithms and methods for linear programming, integer linear programming, and goal programming models. It then describes the principles of several OR procedures in SAS. Subsequent chapters explain how to use these procedures to solve various types of OR problems. Each of these chapters describes the concept of an OR problem, presents an example of the problem, and discusses the specific procedure and its macros for the optimal solution of the problem. The macros include data handling, model building, and report writing.While primarily designed for SAS users in OR and marketing analytics, the book can also be used by readers interested in mathematical modeling techniques. By formulating the OR problems as mathematical models, the authors show how SAS can solve a variety of optimization problems"--



Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project management decisions, printed circuit board assembly, and multiple criteria decision making.

The text begins with the algorithms and methods for linear programming, integer linear programming, and goal programming models. It then describes the principles of several OR procedures in SAS. Subsequent chapters explain how to use these procedures to solve various types of OR problems. Each of these chapters describes the concept of an OR problem, presents an example of the problem, and discusses the specific procedure and its macros for the optimal solution of the problem. The macros include data handling, model building, and report writing.

While primarily designed for SAS users in OR and marketing analytics, the book can also be used by readers interested in mathematical modeling techniques. By formulating the OR problems as mathematical models, the authors show how SAS can solve a variety of optimization problems.

Arvustused

" the authors do a good job of explaining how to apply SAS to a wide variety of problems in operations research and operations management, and the publisher makes copies of SAS code from the book available to purchasers of the book. For the reader who has a sufficient background in operations research, is comfortable with SAS macros, and is interested in learning, this book will provide a welcome and useful resource." The American Statistician, August 2014

"This book successfully bridges the gap between theory and practice. Written primarily for SAS, the authors present a wide range of optimisation problems to demonstrate how the SAS/OR® procedures work. The text is well written, easy to follow, and will appeal both to those who have an interest only in concepts and to those merely interested in solving practical problems." Carl M. OBrien, International Statistical Review (2013), 81

Preface xiii
1 Operational Research, Algorithms, and Methods
1(28)
1.1 Linear Programming
1(6)
1.1.1 Simplex Method
5(1)
1.1.2 Revised Simplex Method
5(1)
1.1.3 Dantzig---Wolfe Decomposition Algorithm
6(1)
1.1.4 Karmarkar Interior Point Algorithm
6(1)
1.1.5 Duality
6(1)
1.1.6 Sensitivity Analysis
7(1)
1.2 Integer Linear Programming
7(2)
1.2.1 Branch-and-Bound Algorithm
8(1)
1.2.2 Cutting Plane Algorithm
9(1)
1.3 Goal Programming
9(2)
1.3.1 Weights Method
10(1)
1.3.2 Preemptive Method
10(1)
1.4 SAS for Operational Research
11(18)
1.4.1 SAS/OR®
12(1)
1.4.2 Example of Using PROC OPTMODEL
13(1)
1.4.2.1 An Introductory Example
14(2)
1.4.2.2 Basic PROC OPTMODEL
16(3)
1.4.2.3 Set and Indexing in PROC OPTMODEL
19(2)
1.4.2.4 Advanced Options in PROC OPTMODEL
21(3)
1.4.3 Other Procedures in SAS/OR®
24(1)
1.4.3.1 PROC OPTLP
24(1)
1.4.3.2 PROC OPTMILP
24(1)
1.4.3.3 PROC OPTQP
24(1)
1.4.3.4 PROC INTPOINT
24(1)
1.4.3.5 PROC CPM
25(1)
1.4.3.6 PROC PM
25(1)
1.4.3.7 PROC GANTT
26(1)
1.4.3.8 PROC DTREE
26(1)
1.4.3.9 PROC GA
26(1)
1.4.3.10 PROC BOM
26(3)
2 Transportation Models
29(30)
2.1 Transportation Problem
29(10)
2.1.1 Concept of Transportation Problem
29(1)
2.1.2 Example of Transportation Problem
30(2)
2.1.3 ORTRANS: SAS Code for Transportation Problem
32(1)
2.1.4 ORTRANS Data-Handling Macro (%data)
33(1)
2.1.5 ORTRANS: Model-Building Macro (%model)
34(1)
2.1.6 ORTRANS: Report-Writing Macro (%report)
35(1)
2.1.7 ORTRANS: Macro (%ortrans)
36(1)
2.1.8 Instructions for Using ORTRANS Macro
36(1)
2.1.9 Sample Results from ORTRANS Macro: Output from SAS
37(1)
2.1.10 Exercise
38(1)
2.2 Assignment Problem
39(11)
2.2.1 Concept of Assignment Problem
39(1)
2.2.2 Example of Assignment Problem
40(2)
2.2.3 ORASSIGN: SAS Code for Assignment Problem
42(1)
2.2.4 ORASSIGN: Data-Handling Macro (%data)
43(1)
2.2.5 ORASSIGN: Model-Building Macro (%model)
44(1)
2.2.6 ORASSIGN: Report-Writing Macro (%report)
45(1)
2.2.7 ORASSIGN: Macro (%orassign)
46(1)
2.2.8 Instructions for Using ORASSIGN Macro
46(1)
2.2.9 Sample Results from ORASSIGN Macro: Output from SAS
47(1)
2.2.10 Exercise
47(3)
2.3 Transshipment Problem
50(9)
2.3.1 Concept of Transshipment Problem
50(1)
2.3.2 Example of Transshipment Problem
51(3)
2.3.3 ORTRANS: SAS Code for Transshipment Problem
54(1)
2.3.4 Sample Results from ORTRANS Macro: Output from SAS
55(1)
2.3.5 Exercise
56(3)
3 Network Models
59(30)
3.1 Minimum-Cost Capacitated Flow Problem
59(12)
3.1.1 Concept of Minimum-Cost Capacitated Flow Problem
59(2)
3.1.2 Example of Minimum-Cost Capacitated Flow Problem
61(3)
3.1.3 ORMCFLOW: SAS Code for Minimum-Cost Capacitated Flow Problem
64(1)
3.1.4 ORMCFLOW: Data-Handling Macro (%data)
65(1)
3.1.5 ORMCFLOW: Model-Building Macro (%model)
66(1)
3.1.6 ORMCFLOW: Report-Writing Macro (%report)
66(1)
3.1.7 ORMCFLOW: Macro (%ormcflow)
67(1)
3.1.8 Instructions for Using ORMCFLOW Macro
67(1)
3.1.9 Sample Results from ORMCFLOW Macro: Output from SAS
68(1)
3.1.10 Exercise
69(2)
3.2 Maximum Flow Problem
71(10)
3.2.1 Concept of Maximum Flow Problem
71(1)
3.2.2 Example of Maximum Flow Problem
72(3)
3.2.3 ORMAXFLOW: SAS Code for Maximum Flow Problem
75(3)
3.2.4 Sample Results from ORMAXFLOW Macro: Output from SAS
78(1)
3.2.5 Exercise
79(2)
3.3 Shortest Path Problem
81(8)
3.3.1 Concept of Shortest Path Problem
81(1)
3.3.2 Example of Shortest Path Problem
82(2)
3.3.3 ORSHORTPATH: SAS Code for Shortest Path Problem
84(2)
3.3.4 Sample Results from ORSHORTPATH Macro: Output from SAS
86(1)
3.3.5 Exercise
87(2)
4 Project Scheduling
89(18)
4.1 Critical Path Analysis
89(9)
4.1.1 Concept of Critical Path Analysis
89(1)
4.1.2 Example of Critical Path Analysis
90(2)
4.1.3 ORCPM: SAS Code for Critical Path Analysis
92(1)
4.1.4 ORCPM: Data-Handling Macro (%data)
93(1)
4.1.5 ORCPM: Model-Building Macro (%model)
94(1)
4.1.6 ORCPM: Report-Writing Macro (%report)
95(1)
4.1.7 ORCPM: Macro (%orcpm)
95(1)
4.1.8 Instructions for Using ORCPM Macro
96(1)
4.1.9 Sample Results from ORCPM Macro: Output from SAS
96(1)
4.1.10 Exercise
97(1)
4.2 Program Evaluation and Review Technique (PERT)
98(9)
4.2.1 Concept of PERT
98(1)
4.2.2 Example of PERT
99(1)
4.2.3 ORPERT: SAS Code for PERT
100(2)
4.2.4 Sample Results from ORPERT Macro: Output from SAS
102(2)
4.2.5 Exercise
104(3)
5 Layout Decision
107(14)
5.1 Assembly Line---Balancing Problem
107(14)
5.1.1 Concept of Assembly Line---Balancing Problem
107(2)
5.1.2 Example of Assembly Line---Balancing Problem
109(3)
5.1.3 ORALBP: SAS Code for Assembly Line---Balancing Problem
112(1)
5.1.4 ORALBP: Data-Handling Macro (%data)
113(1)
5.1.5 ORALBP: Model-Building Macro (%model)
114(2)
5.1.6 ORALBP: Report-Writing Macro (%report)
116(1)
5.1.7 ORALBP: Macro (%oralbp)
116(1)
5.1.8 Instructions for Using ORALBP Macro
117(1)
5.1.9 Sample Results from ORALBP Macro: Output from SAS
117(1)
5.1.10 Exercise
118(3)
6 Traveling Salesman Problem
121(10)
6.1 Traveling Salesman Problem (TSP)
121(10)
6.1.1 Concept of TSP
121(1)
6.1.2 Example of TSP
122(3)
6.1.3 ORTSP: SAS Code for TSP
125(1)
6.1.4 ORTSP: Data-Handling Macro (%data)
126(1)
6.1.5 ORTSP: Model-Building Macro (%model)
127(1)
6.1.6 ORTSP: Report-Writing Macro (%report)
127(1)
6.1.7 ORTSP: Macro (%ortsp)
128(1)
6.1.8 Instructions for Using ORTSP Macro
128(1)
6.1.9 Sample Results from ORTSP Macro: Output from SAS
128(1)
6.1.10 Exercise
129(2)
7 Printed Circuit Board Production Planning
131(38)
7.1 Printed Circuit Board (PCB) Assembly Line Assignment Problem
131(12)
7.1.1 Concept of PCB Assembly Line Assignment Problem
131(3)
7.1.2 Example of PCB Assembly Line Assignment Problem
134(1)
7.1.3 ORALA: SAS Code for PCB Assembly Line Assignment Problem
135(1)
7.1.4 ORALA: Data-Handling Macro (%data)
136(1)
7.1.5 ORALA: Model-Building Macro (%model)
137(2)
7.1.6 ORALA: Report-Writing Macro (%report)
139(1)
7.1.7 ORALA: Macro (%orala)
139(1)
7.1.8 Instructions for Using ORALA Macro
140(1)
7.1.9 Sample Results from ORALA Macro: Output from SAS
140(1)
7.1.10 Exercise
141(2)
7.2 PCB Component Allocation Problem
143(10)
7.2.1 Concept of PCB Component Allocation Problem
143(2)
7.2.2 Example of PCB Component Allocation Problem
145(2)
7.2.3 ORCAP: SAS Code for PCB Component Allocation Problem
147(1)
7.2.4 ORCAP: Data-Handling Macro (%data)
147(1)
7.2.5 ORCAP: Model-Building Macro (%model)
148(2)
7.2.6 ORCAP: Report-Writing Macro (%report)
150(1)
7.2.7 ORCAP: Macro (%orcap)
150(1)
7.2.8 Instruction for Using ORCAP Macro
151(1)
7.2.9 Sample Results from ORCAP Macro: Output from SAS
151(1)
7.2.10 Exercise
152(1)
7.3 PCB Component-Sequencing Problem for PAP Machines
153(16)
7.3.1 Concept of PCB Component-Sequencing Problem
153(4)
7.3.2 Example of PCB Component-Sequencing Problem
157(2)
7.3.3 ORCSP: SAS Code for PCB Component-Sequencing Problem
159(1)
7.3.4 ORCSP: Data-Handling Macro (%data)
160(1)
7.3.5 ORCSP: Model-Building Macro (%model)
161(3)
7.3.6 ORCSP: Report-Writing Macro (%report)
164(1)
7.3.7 ORCSP: Macro (%orcsp)
164(1)
7.3.8 Instructions for Using ORCSP Macro
165(1)
7.3.9 Sample Results from ORCSP Macro: Output from SAS
165(1)
7.3.10 Exercise
166(3)
8 Multiple-Criteria Decision Making
169(36)
8.1 Multiple-Criteria Logistics Distribution Problem: Phase 1
169(15)
8.1.1 Concept of Multiple-Criteria Logistics Distribution Problem
169(1)
8.1.2 Concept of AHP
170(1)
8.1.3 Example of AHP
171(1)
8.1.4 ORAHP: SAS Code for AHP
172(1)
8.1.5 ORAHP: Data-Handling Macro (%data)
173(3)
8.1.6 ORAHP: Model-Building Macro (%model)
176(3)
8.1.7 ORAHP: Report-Writing Macro (%report1 and %report2)
179(1)
8.1.8 ORAHP: Macro (%orahp)
180(1)
8.1.9 Instructions for Using ORAHP Macro
181(1)
8.1.10 Sample Results from ORAHP Macro: Output from SAS
181(2)
8.1.11 Exercise
183(1)
8.2 Multiple-Criteria Logistics Distribution Problem: Phase 2
184(21)
8.2.1 Example of Multiple-Criteria Logistics Distribution Problem
184(7)
8.2.2 ORMCDM: SAS Code for Multiple-Criteria Logistics Distribution Problem
191(1)
8.2.3 ORMCDM: Data-Handling Macro (%data)
192(1)
8.2.4 ORMCDM: Model-Building Macro (%model)
193(3)
8.2.5 ORMCDM: Report-Writing Macro (%report)
196(1)
8.2.6 ORMCDM: Macro (%ormcdm)
196(1)
8.2.7 Instructions for Using ORMCDM Macro
197(1)
8.2.8 Sample Results from ORMCDM Macro: Output from SAS
197(2)
8.2.9 Exercise
199(6)
9 Decision Making and Efficiency Measurement
205(42)
9.1 Ordered Weighted Averaging (OWA) Operators and Preference Ranking
205(12)
9.1.1 Concept of OWA
205(2)
9.1.2 Example of OWA
207(1)
9.1.3 OROWA: SAS Code for OWA
208(1)
9.1.4 OROWA: Data-Handling Macro (%data)
208(2)
9.1.5 OROWA: Model-Building Macro (%model)
210(1)
9.1.6 OROWA: Report-Writing Macro (%report)
211(2)
9.1.7 OROWA: Macro (%orowa)
213(1)
9.1.8 Instructions for Using OROWA Macro
213(1)
9.1.9 Sample Results from OROWA Macro: Output from SAS
214(1)
9.1.10 Exercise
214(3)
9.2 Efficiency Measurement Using Data Envelopment Analysis (DEA)
217(13)
9.2.1 Concept of DEA
217(2)
9.2.2 Example of DEA
219(1)
9.2.3 ORDEA: SAS Code for DEA
220(1)
9.2.4 ORDEA: Data-Handling Macro (%data)
221(1)
9.2.5 ORDEA: Model-Building Macro (%model)
222(3)
9.2.6 ORDEA: Report-Writing Macro (%report)
225(2)
9.2.7 ORDEA: Macro (%ordea)
227(1)
9.2.8 Instructions for Using ORDEA Macro
227(1)
9.2.9 Sample Results from ORDEA Macro: Output from SAS
228(1)
9.2.10 Exercise
228(2)
9.3 Productivity Measurement Using Malmquist Index
230(17)
9.3.1 Concept of Malmquist Index
230(4)
9.3.2 Example of Malmquist Index
234(2)
9.3.3 ORMALM: SAS Code for Malmquist Index
236(1)
9.3.4 ORMALM: Data-Handling Macro (%data)
237(2)
9.3.5 ORMALM: Model-Building Macro (%model_outOri)
239(2)
9.3.6 ORMALM: Report-Writing Macro (%report)
241(1)
9.3.7 ORMALM: Macro (%ormalm)
242(1)
9.3.8 Instructions for Using ORMALM Macro
243(1)
9.3.9 Sample Results from ORMALM Macro: Output from SAS
243(1)
9.3.10 Exercise
244(3)
Appendices 247(14)
References 261(4)
Index 265
Ali Emrouznejad is a reader in the Operations & Information Management Group at Aston Business School. Dr. Emrouznejad is a senior editor and one of the founding members of the Data Envelopment Analysis Journal and an associate editor of the IMA Journal of Management Mathematics. He is also co-founder of Performance Improvement Management Software (PIM-DEA) and maintains a website for DEA users at www.deazone.com He earned a Ph.D. in operational research and systems from Warwick Business School. His research interests include performance measurement and management, efficiency and productivity analysis, and data mining.

William Ho is the BAM course director and a senior lecturer in the Operations & Information Management Group at Aston Business School. Dr. Ho is an editorial board member of the International Journal of Advanced Manufacturing Technology and an associate editor of OR Insights. He earned a Ph.D. in operations research from the Hong Kong Polytechnic University. His research interests include supply chain management, transportation and logistics management, production and operations management, and operations research.