Algebraic modeling systems: modeling and solving real world optimization problems
Gespeichert in:
| Weitere beteiligte Personen: | |
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| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Heidelberg [u.a.]
Springer
2012
|
| Schriftenreihe: | Applied optimization
104 |
| Schlagwörter: | |
| Links: | http://deposit.dnb.de/cgi-bin/dokserv?id=3859622&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025130376&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Literaturangaben |
| Umfang: | XXVI, 236 S. graph. Darst. 24 cm |
| ISBN: | 9783642235917 3642235913 |
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| 245 | 1 | 0 | |a Algebraic modeling systems |b modeling and solving real world optimization problems |c ed. by Josef Kallrath |
| 264 | 1 | |a Heidelberg [u.a.] |b Springer |c 2012 | |
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| 700 | 1 | |a Kallrath, Josef |0 (DE-588)1042215855 |4 edt | |
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Datensatz im Suchindex
| _version_ | 1819367255025123328 |
|---|---|
| adam_text | IMAGE 1
CONTENTS
PART I INTRODUCTION AND FOUNDATIONS 1 ALGEBRAIC MODELING LANGUAGES:
INTRODUCTION AND OVERVIEW 3
JOSEF KALLRATH 1.1 INTRODUCTION 3
1.2 MODELS AND THE CONTRAST BETWEEN DECLARATIVE AND PROCEDURAL 5 1.3
EXAMPLE PROBLEM: DECLARATIVE VERSUS PROCEDURAL 8
1.4 MODELING AND TEACHING: CONCLUSIONS 9
REFERENCES 10
2 TOWARDS A SELF-REFLECTIVE, CONTEXT-AWARE SEMANTIC REPRESENTATION O F
MATHEMATICAL SPECIFICATIONS 11
PETER SCHODL, ARNOLD NEUMAIER, KEVIN KOFLER, FERENC DOMES, AND HERMANN
SCHICHL 2. 1 THE M O S M A T H PROJECT 11
2.2 VISION: THE FMATHL PROJECT 12
2.3 DATA STRUCTURE: THE SEMANTIC MEMORY 14
2.4 PROCESSING: THE SEMANTIC VIRTUAL MACHINE 16
2.5 REPRESENTATION: THE TYPE SYSTEM 18
2 . 6 HIGHER LEVEL PROCESSING: C O N C I S E 2 1
2.7 MATHEMATICAL MODELING 21
2.8 REFLECTION 23
2.9 EXAMPLES OF EXPRESSIONS 24
REFERENCES 31
PART II SELECTED ALGEBRAIC MODELING SYSTEMS
3 GUSS: SOLVING COLLECTIONS O F DATA RELATED MODELS WITHIN GAMS 35
MICHAEL R. BUSSIECK, MICHAEL C. FERRIS, AND TIMO LOHMANN 3.1
INTRODUCTION 35
XVII
HTTP://D-NB.INFO/1013868080
IMAGE 2
X V I I I C O N T E N T S
3.2 DESIGN METHODOLOGY 37
3.2.1 GUSS OPTIONS 4 0
3.2.2 IMPLEMENTATION DETAILS 41
3.3 EXAMPLES 42
3.3.1 DATA ENVELOPMENT ANALYSIS 42
3.3.2 CROSS VALIDATION FOR SUPPORT VECTOR MACHINES 4 6
3.3.3 SDDP 5 0
3.4 CONCLUSION 5 4
REFERENCES 55
4 GENERALIZED DISJUNCTIVE PROGRAMMING: SOLUTION STRATEGIES 57
JUAN P. RUIZ, JAN-H. JAGLA, IGNACIO E. GROSSMANN, ALEX MEERAUS, AND ALDO
VECCHIETTI 4.1 INTRODUCTION 58
4.2 GENERALIZED DISJUNCTIVE PROGRAMMING 59
4.2.1 FORMULATION 59
4.2.2 ILLUSTRATIVE EXAMPLE 60
4.2.3 SOLUTION METHODS 62
4.3 GENERALIZED DISJUNCTIVE PROGRAMMING SOLVERS 69
4.3.1 LOGICAL MIXED INTEGER PROGRAMMING (LOGMIP) 69
4.3.2 EXTENDED MATHEMATICAL PROGRAMMING (EMP) 69
4.4 CONCLUSIONS 73
REFERENCES 74
5 XPRESS-MOSEL: MULTI-SOLVER, MULTI-PROBLEM, MULTI-MODEL, MULTI-NODE 77
SUSANNE HEIPCKE 5.1 INTRODUCTION 77
5.2 THE MOSEL ENVIRONMENT: QUICK TOUR 79
5.2.1 BASIC MODELING AND SOLVING TASKS 79
5.2.2 PROGRAMMING WITH MOSEL 83
5.2.3 MODULES AND PACKAGES 86
5.2.4 EMBEDDING AND DEPLOYMENT 89
5.3 THE MULTIS 91
5.3.1 MULTI-SOLVER 91
5.3.2 MULTI-PROBLEM 95
5.3.3 MULTI-MODEL 97
5.3.4 MULTI-NODE 101
5.4 SUMMARY 104
APPENDIX: COMPLETE MOSEL EXAMPLES 105
SOLUTION ENUMERATION 105
COLUMN GENERATION FOR THE CUTTING STOCK PROBLEM 106
REFERENCES 110
IMAGE 3
C O N T E N T S X I X
6 INTERVAL-BASED LANGUAGE FOR MODELING SCHEDULING
PROBLEMS: AN EXTENSION TO CONSTRAINT PROGRAMMING I L L
PHILIPPE LABORIE, JEROME ROGERIE, PAUL SHAW, PETR VIH M, AND FERENC
KATAI 6.1 INTRODUCTION I L L
6.2 CONDITIONAL INTERVAL MODEL 113
6.2.1 USAGE AND RATIONALE 113
6.2.2 INTERVAL VARIABLES 113
6.2.3 PRESENCE CONSTRAINTS 114
6.2.4 PRECEDENCE CONSTRAINTS 115
6.2.5 INTENSITY FUNCTIONS 115
6.2.6 INTERVAL COMPOSITION CONSTRAINTS 116
6.3 COMPLEXITY 117
6.4 GRAPHICAL CONVENTIONS AND BASIC EXAMPLES 118
6.4.1 ALTERNATIVE MODES WITH COMPATIBILITY CONSTRAINTS 118 6.4.2
SERIES/PARALLEL ALTERNATIVE 119
6.4.3 ALTERNATIVE RECIPES 119
6.4.4 TEMPORAL DISJUNCTION 120
6.5 SEQUENCE VARIABLES 120
6.5.1 USAGE AND RATIONALE 120
6.5.2 FORMAL SEMANTICS 120
6.6 CUMUL FUNCTION EXPRESSIONS 122
6.6.1 USAGE AND RATIONALE 122
6.6.2 FORMAL SEMANTICS 123
6.6.3 EXAMPLE 124
6.7 STATE FUNCTION VARIABLES 125
6.7.1 USAGE AND RATIONALE 125
6.7.2 FORMAL SEMANTICS 126
6.7.3 EXAMPLE 127
6.8 CONSTRAINT PROPAGATION AND SEARCH 127
6.8.1 INTERVAL VARIABLES 127
6.8.2 LOGICAL NETWORK 128
6.8.3 TEMPORAL NETWORK 129
6.8.4 INTERVAL COMPOSITION CONSTRAINTS 131
6.8.5 OTHER CONSTRAINTS 131
6.8.6 SEARCH, 132
6.9 EXAMPLES 132
6.9.1 FLOW-SHOP WITH EARLINESS AND TARDINESS COSTS 132
6.9.2 SATELLITE SCHEDULING 134
6.9.3 PERSONAL TASK SCHEDULING 137
6.10 CONCLUSION 141
REFERENCES 142
IMAGE 4
X X C O N T E N T S
7 USING Z I M P L FOR MODELING PRODUCTION PLANNING PROBLEMS 145
ULRICH DORNDORF, STEFAN DROSTE, AND THORSTEN KOCH 7.1 INTRODUCTION 145
7.2 ZLMPL 147
7.3 FORMULATING THE MLCLSP WITH ZLMPL 149
7.4 Z L M P L IN I N F O R M S TRAINING AND WORKFLOW 156
7.5 CONCLUSION 157
REFERENCES 157
PART III ASPECTS O F MODELING AND SOLVING REAL WORLD PROBLEMS
8 WHY OUR COMPANY USES PROGRAMMING LANGUAGES FOR MATHEMATICAL MODELING
AND OPTIMIZATION 161
HERMANN GOLD 8.1 INTRODUCTION 161
8.2 AN ANSWER GIVEN BY EXPERIENCE FROM THE PAST 162
8.3 REASONS ARISING FROM MATHEMATICAL MODELING AND SOLVER ASPECTS 164
8.4 THE ASPECT OF MODELING TRANSPARANCY 167
REFERENCES 168
9 DATA PREPARATION FOR OPTIMIZATION WITH R 171
HANS-JOACHIM PITZ 9.1 INTRODUCTION 171
9.2 WHAT IS R? 172
9.3 THE HISTORY OF R 172
9.4 HOW CAN THE PREPARATION OF OPTIMIZATION DATA BE SUPPORTED WITH R?
173
9.5 HOW CAN R BE LINKED TO OPTIMIZATION SOFTWARE 177
9.6 SUMMARY 178
APPENDIX A: R APPLICATION FOR GENERATING A GAMS DATA FILE 178
APPENDIX B: R-OUTPUT OF THE GAMS INCLUDE FILE 179
APPENDIX C: R FUNCTIONS FOR WRITING GAMS SETS AND PARAMETERS 179
REFERENCES 183
10 VISPLAIN: INSIGHT BY VISUALIZATION 185
AXEL HECKER AND ARND VOM HOFE 10.1 INTRODUCTION 185
10.2 A SIMPLE EXAMPLE 186
10.3 A MORE REALISTIC EXAMPLE 188
10.3.1 HOVERING OVER A NODE WITH THE MOUSE POINTER 189
10.3.2 SELECTING ATTRIBUTES 191
10.3.3 DERIVED AND CALCULATED ATTRIBUTES 192
10.3.4 SELECTING NODES FOR REPORTING IN TABLE FORMAT 194
10.4 A COMPLEX EXAMPLE 195
10.5 SUMMARY 197
IMAGE 5
C O N T E N T S X X I
11 ECONOMIC SIMULATION MODELS IN AGRICULTURAL ECONOMICS:
THE CURRENT AND POSSIBLE FUTURE ROLE O F ALGEBRAIC MODELING LANGUAGES 1
99
WOLFGANG BRITZ AND JOSEF KALLRATH 11.1 INTRODUCTION 199
11.2 MODEL TYPES IN AGRICULTURAL ECONOMICS 200
11.2.1 SINGLE FARM MODELS 200
11.2.2 AGGREGATE PROGRAMMING MODELS 200
11.2.3 PARTIAL MARKET MODELS 201
11.2.4 COMPUTABLE GENERAL EQUILIBRIUM MODELS 203
11.2.5 GENERAL DEVELOPMENTS AND SUMMARY 204
11.3 FROM MODEL TO TOOLS AND CONSEQUENCES FOR THE IT CONCEPT 205 11.4
CHALLENGES FOR ALGEBRAIC MODEL LANGUAGES 206
11.4.1 LANGUAGE STRUCTURE AND MODULARIZATION 206
11.4.2 GUIS AND REPORT GENERATORS 208
11.4.3 PARALLEL EXECUTION 208
11.4.4 WHERE TO STOP? 209
11.5 SUMMARY AND CONCLUSION 210
REFERENCES 210
12 A PRACTIONER S WISH LIST TOWARDS ALGEBRAIC MODELING SYSTEMS 213 JOSEF
KALLRATH 12.1 INTRODUCTION 213
12.2 ALGEBRAIC REFORMULATIONS O F NONLINEAR RELATIONS 214
12.3 CONSTRAINTS DEFINED ON SETS 216
12.3.1 MODELING NON-ZERO VARIABLES 216
12.3.2 MODELING SETS O F ALL-DIFFERENT ELEMENTS 217
12.3.3 UPPER BOUNDS ON SUM O F THE MAXIMAL K VARIABLES 218
12.4 INCLUSION O F PROGRAMMING CODE 219
12.5 SPECIAL MATHEMATICAL FEATURES 220
12.6 BETTER SUPPORT O F POLYLITHIC MODELING AND SOLUTION APPROACHES 220
12.7 I4TGX OUTPUT OF ALL RELEVANT OBJECTS 221
12.8 THE FUTURE 221
REFERENCES 222
APPENDIX A GLOSSARY 223
INDEX 23 1
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| id | DE-604.BV040274876 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T16:11:22Z |
| institution | BVB |
| isbn | 9783642235917 3642235913 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025130376 |
| oclc_num | 794507966 |
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| physical | XXVI, 236 S. graph. Darst. 24 cm |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Springer |
| record_format | marc |
| series | Applied optimization |
| series2 | Applied optimization |
| spellingShingle | Algebraic modeling systems modeling and solving real world optimization problems Applied optimization Entwurfssprache (DE-588)4295335-2 gnd Optimierungsproblem (DE-588)4390818-4 gnd |
| subject_GND | (DE-588)4295335-2 (DE-588)4390818-4 |
| title | Algebraic modeling systems modeling and solving real world optimization problems |
| title_auth | Algebraic modeling systems modeling and solving real world optimization problems |
| title_exact_search | Algebraic modeling systems modeling and solving real world optimization problems |
| title_full | Algebraic modeling systems modeling and solving real world optimization problems ed. by Josef Kallrath |
| title_fullStr | Algebraic modeling systems modeling and solving real world optimization problems ed. by Josef Kallrath |
| title_full_unstemmed | Algebraic modeling systems modeling and solving real world optimization problems ed. by Josef Kallrath |
| title_short | Algebraic modeling systems |
| title_sort | algebraic modeling systems modeling and solving real world optimization problems |
| title_sub | modeling and solving real world optimization problems |
| topic | Entwurfssprache (DE-588)4295335-2 gnd Optimierungsproblem (DE-588)4390818-4 gnd |
| topic_facet | Entwurfssprache Optimierungsproblem |
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