Optimization in operations research:
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Harlow
Pearson
2014
|
| Edition: | new internat. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVI, 919 S. graf. Darst. |
| ISBN: | 9781292042473 1292042478 |
Staff View
MARC
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| 100 | 1 | |a Rardin, Ronald L. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Optimization in operations research |c Ronald L. Rardin |
| 250 | |a new internat. ed. | ||
| 264 | 1 | |a Harlow |b Pearson |c 2014 | |
| 300 | |a XVI, 919 S. |b graf. Darst. | ||
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| 650 | 4 | |a Mathematical optimization | |
| 650 | 4 | |a Operations research | |
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Record in the Search Index
| _version_ | 1804152091382382593 |
|---|---|
| adam_text | Contents
Preface
ix
About the Author
xvi
Chapter
1
Problem Solving with Mathematical Models
1
1.1
OR Application Stories
1
1.2
Optimization and the Operations Research Process
3
1.3
System Boundaries, Sensitivity Analysis, Tractability and Validity
8
1.4
Descriptive Models and Simulation
11
1.5
Numerical Search and Exact versus Heuristic Solutions
14
1.6
Deterministic versus Stochastic Models
16
1.7
Perspectives
19
Exercises
20
Chapter
2
Deterministic Optimization Models
in Operations Research
23
2.1
Decision Variables, Constraints, and Objective Functions
23
2.2
Graphic Solution and Optimization Outcomes
27
2.3
Large-Scale Optimization Models and Indexing
39
2.4
Linear and Nonlinear Programs
46
2.5
Discrete or Integer Programs
52
2.6
Multiobjective Optimization Models
59
2.7
Classification Summary
63
Exercises
64
Chapter
3
Improving Search
77
3.1
Improving Search, Local and Global Optima
77
3.2
Search with Improving and Feasible Directions
88
3.3
Algebraic Conditions for Improving
and Feasible Directions
99
3.4
Unimodel and Convex Model Forms Tractable
for Improving Search
109
vii
Vlil
· Contents
3.5
Searching and Starting Feasible Solutions
118
Exercises
127
Chapter
4
Linear Programming Models
131
4.1
Allocation Models
131
4.2
Blending Models
135
4.3
Operations Planning Models
139
4.4
Shift Scheduling and Staff Planning Models
148
4.5
Time-Phased Models
153
4.6
Models with Linearizable Nonlinear Objectives
157
Exercises
164
Chapter
5
Simplex Search for Linear Programming
175
5.1
LP Optimal Solutions and Standard Form
175
5.2
Extreme-Point Search and Basic Solutions
186
5.3
The Simplex Algorithm
197
5.4
Dictionary and Tableau Representations of Simplex
207
5.5
Two Phase Simplex
211
5.6
Degeneracy and Zero-Length Simplex Steps
220
5.7
Convergence and Cycling with Simplex
224
5.8
Doing It Efficiently: Revised Simplex
225
5.9
Simplex with Simple Upper and Lower Bounds
238
Exercises
245
Chapter
6
Interior Point Methods for Linear
Programming
251
6.1
Searching through the Interior
251
6.2
Scaling with the Current Solution
262
6.3 Affine
Scaling Search
269
6.4
Log Barrier Methods for Interior Point Search
275
6.5
Dual and Primal-Dual Extensions
287
Exercises
293
Chapter
7
Duality and Sensitivity in Linear Programming
299
7.1
Generic Activities versus Resources Perspective
299
7.2
Qualitative Sensitivity to Changes in Model
Coefficients
304
7.3
Quantifying Sensitivity to Changes in LP Model
Coefficients: A Dual Model
315
7.4
Formulating Linear Programming Duals
324
7.5
Primal-to-Dual Relationships
329
7.6
Computer Outputs and What If Changes of Single
Parameters
338
Contents ·
ЇХ
7.7
Bigger Model Changes, Reoptimization, and Parametric
Programming
354
Exercises
363
Chapter
8
Muuiobjective Optimization and Goal
Programming
373
8.1
Multiobjective Optimization Models
373
8.2
Efficient Points and the Efficient Frontier
378
8.3
Preemptive Optimization and Weighted Sums
of Objectives
384
8.4
Goal Programming
389
Exercises
400
Chapter
9
Shortest Paths and Discrete
D
ynamic
Programming
409
9.1
Shortest Path Models
409
9.2
Dynamic Programming Approach to Shortest Paths
417
9.3
Shortest Paths From One Node to All Others:
Bellman-Ford
426
9.4
Shortest Paths From All Nodes to All Others:
Floyd-Warshall
433
9.5
Shortest Path From One Node to All Others With Costs
Nonnegative:
Dijkstra
440
9.6
Shortest Paths From One Node to All Others
in Acyclic Digraphs
446
9.7
CPM Project Scheduling and Longest Paths
450
9.8
Discrete Dynamic Programming Models
458
Exercises
468
Chapter
10
Network Flows
475
10.1
Graphs, Networks, and Flows
475
10.2
Cycle Directions for Network Flow Search
483
10.3
Rudimentary Cycle Direction Search Algorithms
for Network Flows
494
10.4
Integrality of Optimal Network Flows
500
10.5
Transportation and Assignment Models
502
10.6
Other Single-Commodity Network Flow Models
511
10.7
Network Simplex Algorithm for Optimal Flows
519
10.8
Cycle Canceling Algorithms for Optimal Flows
529
10.9
Multicommodity and Gain/Loss Flows
536
Exercises
543
Χ
· Contents
Chapter
11
Discrete Optimization Models
555
11.1
Lumpy Linear Programs and Fixed Charges
555
11.2
Knapsack and Capital Budgeting Models
560
11.3
Set Packing, Covering, and Partitioning Models
566
11.4
Assignment and Matching Models
574
11.5
Traveling Salesman and Routing Models
584
11.6
Facility Location and Network Design Models
594
11.7
Processor Scheduling and Sequencing Models
602
Exercises
613
Chapter
12
Discrete Optimization Methods
627
12.1
Solving by Total Enumeration
627
12.2
Relaxations of Discrete Optimization Models and Their
Uses
630
12.3
Stronger LP relaxations, Valid Inequalities,
and Lagrangian Relaxations
641
12.4
Branch and Bound Search
651
12.5
Rounding, Parent Bounds, Enumerations Sequences,
and Stopping Early in Branch and Bound
664
12.6
Improving Search Heuristics for Discrete Optimization
INLPs
680
12.7
Tabu, Simulated Annealing, and Genetic Algorithm
Extensions of Improving Search
687
12.8
Constructive Heuristics
698
Exercises
705
Chapter
13
Unconstrained Nonlinear Programming
715
13.1
Unconstrained Nonlinear Programming Models
715
13.2
One-Dimensional Search
726
13.3
Derivatives,Taylor Series, and Conditions for Local
Optima
737
13.4
Convex/Concave Functions and Global Optimality
749
13.5
Gradient Search
757
13.6
Newton s Method
761
13.7
Quasi-Newton
Methods and BFGS Search
766
13.8
Optimization without Derivatives and Nelder-Mead
774
Exercises
781
Chapter
14
Constrained Nonunear Programming
787
14.1
Constrained Nonlinear Programming Models
787
14.2
Convex, Separable, Quadratic and Posynomial
Geometric Programming Special NLP Forms
795
14.3 Lagrange
Multiplier Methods
810
Contents · Xl
14.4 Karush-Kuhn-Tucker Optimality
Conditions
817
14.5 Penalty
and Barrier Methods
827
14.6
Reduced
Gradient
Algorithms
837
14.7
Quadratic Programming Methods
849
14.8
Separable Programming Methods
858
14.9
Posynomial Geometric Programming Methods
866
Exercises
875
Selected Answers
887
Index
905
|
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| dewey-full | 519.7 |
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| dewey-search | 519.7 |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | new internat. ed. |
| format | Book |
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| indexdate | 2024-07-10T01:05:12Z |
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| isbn | 9781292042473 1292042478 |
| language | English |
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| spelling | Rardin, Ronald L. Verfasser aut Optimization in operations research Ronald L. Rardin new internat. ed. Harlow Pearson 2014 XVI, 919 S. graf. Darst. txt rdacontent n rdamedia nc rdacarrier Mathematical optimization Operations research Programming Mathematics Optimierung (DE-588)4043664-0 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Operations Research (DE-588)4043586-6 s Optimierung (DE-588)4043664-0 s DE-604 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027225387&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Rardin, Ronald L. Optimization in operations research Mathematical optimization Operations research Programming Mathematics Optimierung (DE-588)4043664-0 gnd Operations Research (DE-588)4043586-6 gnd |
| subject_GND | (DE-588)4043664-0 (DE-588)4043586-6 |
| title | Optimization in operations research |
| title_auth | Optimization in operations research |
| title_exact_search | Optimization in operations research |
| title_full | Optimization in operations research Ronald L. Rardin |
| title_fullStr | Optimization in operations research Ronald L. Rardin |
| title_full_unstemmed | Optimization in operations research Ronald L. Rardin |
| title_short | Optimization in operations research |
| title_sort | optimization in operations research |
| topic | Mathematical optimization Operations research Programming Mathematics Optimierung (DE-588)4043664-0 gnd Operations Research (DE-588)4043586-6 gnd |
| topic_facet | Mathematical optimization Operations research Programming Mathematics Optimierung Operations Research |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027225387&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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