LEADER 08819nam 2200613 450 001 996466399003316 005 20220527114050.0 010 $a3-030-68928-X 035 $a(CKB)5590000000442451 035 $a(MiAaPQ)EBC6531628 035 $a(Au-PeEL)EBL6531628 035 $a(OCoLC)1244620167 035 $a(PPN)254720099 035 $a(EXLCZ)995590000000442451 100 $a20211015d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPyomo-optimization modeling in python /$fMichael L. Bynum [and seven others] 205 $a3rd ed. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (231 pages) 225 1 $aSpringer Optimization and Its Applications ;$vVolume 67 311 $a3-030-68927-1 327 $aIntro -- Preface -- Goals of the Book -- Who Should Read This Book -- Revisions for the Third Edition -- Acknowledgments -- Disclaimers -- Comments and Questions -- Contents -- Chapter 1 Introduction -- 1.1 Modeling Languages for Optimization -- 1.2 Modeling with Pyomo -- 1.2.1 Simple Examples -- 1.2.2 Graph Coloring Example -- 1.2.3 Key Pyomo Features -- Python -- Customizable Capability -- Command-Line Tools and Scripting -- Concrete and Abstract Model Definitions -- Object-Oriented Design -- Expressive Modeling Capability -- Solver Integration -- Open Source -- 1.3 Getting Started -- 1.4 Book Summary -- 1.5 Discussion -- Part I An Introduction to Pyomo -- Chapter 2 Mathematical Modeling and Optimization -- 2.1 Mathematical Modeling -- 2.1.1 Overview -- 2.1.2 A Modeling Example -- 2.2 Optimization -- 2.3 Modeling with Pyomo -- 2.3.1 A Concrete Formulation -- 2.4 Linear and Nonlinear Optimization Models -- 2.4.1 Definition -- 2.4.2 Linear Version -- 2.5 Solving the Pyomo Model -- 2.5.1 Solvers -- 2.5.2 Python Scripts -- Chapter 3 Pyomo Overview -- 3.1 Introduction -- 3.2 The Warehouse Location Problem -- 3.3 Pyomo Models -- 3.3.1 Components for Variables, Objectives, and Constraints -- 3.3.2 Indexed Components -- 3.3.3 Construction Rules -- 3.3.4 A Concrete Model for the Warehouse Location Problem -- 3.3.5 Modeling Components for Sets and Parameters -- Chapter 4 Pyomo Models and Components: An Introduction -- 4.1 An Object-Oriented AML -- 4.2 Common Component Paradigms -- 4.2.1 Indexed Components -- 4.3 Variables -- 4.3.1 Var Declarations -- 4.3.2 Working with Var Objects -- 4.4 Objectives -- 4.4.1 Objective Declarations -- 4.4.2 Working with Objective Objects -- 4.5 Constraints -- 4.5.1 Constraint Declarations -- 4.5.2 Working with Constraint Objects -- 4.6 Set Data -- 4.6.1 Set Declarations -- 4.6.2 Working with Set Objects. 327 $a4.7 Parameter Data -- 4.7.1 Param Declarations -- 4.7.2 Working with Param Objects -- 4.8 Named Expressions -- 4.8.1 Expression Declarations -- 4.8.2 Working with Expression Objects -- 4.9 Suffix Components -- 4.9.1 Suffix Declarations -- 4.9.2 Working with Suffixes -- 4.10 Other Modeling Components -- Chapter 5 Scripting Custom Workflows -- 5.1 Introduction -- 5.2 Interrogating the Model -- 5.2.1 The The value Function -- 5.2.2 Accessing Attributes of Indexed Components -- 5.2.2.1 Slicing Over Indices of Components -- 5.2.2.2 Iterating Over All Var Objects on a Model -- 5.3 Modifying Pyomo Model Structure -- 5.4 Examples of Common Scripting Tasks -- 5.4.1 Warehouse Location Loop and Plotting -- 5.4.2 A Sudoku Solver -- Chapter 6 Interacting with Solvers -- 6.1 Introduction -- 6.2 Using Solvers -- 6.3 Investigating the Solution -- 6.3.1 Solver Results -- Part II Advanced Topics -- Chapter 7 Nonlinear Programming with Pyomo -- 7.1 Introduction -- 7.2 Nonlinear Progamming Problems in Pyomo -- 7.2.1 Nonlinear Expressions -- 7.2.2 The Rosenbrock Problem -- 7.3 Solving Nonlinear Programming Formulations -- 7.3.1 Nonlinear Solvers -- 7.3.2 Additional Tips for Nonlinear Programming -- Variable Initialization -- Undefined Evaluations -- Model Singularities and Problem Scaling -- 7.4 Nonlinear Programming Examples -- 7.4.1 Variable Initialization for a Multimodal Function -- 7.4.2 Optimal Quotas for Sustainable Harvesting of Deer -- 7.4.3 Estimation of Infectious Disease Models -- 7.4.4 Reactor Design -- Chapter 8 Structured Modeling with Blocks -- 8.1 Introduction -- 8.2 Block structures -- 8.3 Blocks as Indexed Components -- 8.4 Construction Rules within Blocks -- 8.5 Extracting values from hierarchical models -- 8.6 Blocks Example: Optimal Multi-Period Lot-Sizing -- 8.6.1 A Formulation Without Blocks -- 8.6.2 A Formulation With Blocks. 327 $aChapter 9 Performance: Model Construction and Solver Interfaces -- 9.1 Profiling to Identify Performance Bottlenecks -- 9.1.1 Report Timing -- 9.1.2 TicTocTimer -- 9.1.3 Profilers -- 9.2 Improving Model Construction Performance with LinearExpression -- 9.3 Repeated Solves with Persistent Solvers -- 9.3.1 When to Use a Persistent Solver -- 9.3.2 Basic Usage -- 9.3.3 Working with Indexed Variables and Constraints -- 9.3.4 Additional Performance -- 9.3.5 Example -- 9.4 Sparse Index Sets -- Chapter 10 Abstract Models and Their Solution -- 10.1 Overview -- 10.1.1 Abstract and Concrete Models -- 10.1.2 An Abstract Formulation of Model (H) -- 10.1.3 An Abstract Model for the Warehouse Location Problem -- 10.2 The pyomo Command -- 10.2.1 The help Subcommand -- 10.2.2 The solve Subcommand -- 10.2.2.1 Specifying the Model Object -- 10.2.2.2 Selecting Data with Namespaces -- 10.2.2.3 Customizing Pyomo's Workflow -- 10.2.2.4 Customizing Solver Behavior -- 10.2.2.5 Analyze Solver Results -- 10.2.2.6 Managing Diagnostic Output -- 10.2.3 The convert Subcommand -- 10.3 Data Commands for Abstract Model -- 10.3.1 The set Command -- 10.3.1.1 Simple Sets -- 10.3.1.2 Sets of Tuple Data -- 10.3.1.3 Set Arrays -- 10.3.2 The param Command -- 10.3.2.1 One-dimensional Parameter Data -- 10.3.2.2 Multi-Dimensional Parameter Data -- 10.3.3 The include Command -- 10.3.4 Data Namespaces -- 10.4 Build Components -- Part III Modeling Extensions -- Chapter 11 Generalized Disjunctive Programming -- 11.1 Introduction -- 11.2 Modeling GDP in Pyomo -- 11.3 Expressing logical constraints -- 11.4 Solving GDP models -- 11.4.1 Big-M transformation -- 11.4.2 Hull transformation -- 11.5 A mixing problem with semi-continuous variables -- Chapter 12 Differential Algebraic Equations -- 12.1 Introduction -- 12.2 Pyomo DAE Modeling Components -- 12.3 Solving Pyomo Models with DAEs. 327 $a12.3.1 Finite Difference Transformation -- 12.3.2 Collocation Transformation -- 12.4 Additional Features -- 12.4.1 Applying Multiple Discretizations -- 12.4.2 Restricting Control Input Profiles -- 12.4.3 Plotting -- Chapter 13 Mathematical Programs with Equilibrium Constraints -- 13.1 Introduction -- 13.2 Modeling Equilibrium Conditions -- 13.2.1 Complementarity Conditions -- 13.2.2 Complementarity Expressions -- 13.2.3 Modeling Mixed-Complementarity Conditions -- 13.3 MPEC Transformations -- 13.3.1 Standard Form -- 13.3.2 Simple Nonlinear -- 13.3.3 Simple Disjunction -- 13.3.4 AMPL Solver Interface -- 13.4 Solver Interfaces and Meta-Solvers -- 13.4.1 Nonlinear Reformulations -- 13.4.2 Disjunctive Reformulations -- 13.4.3 PATH and the ASL Solver Interface -- 13.5 Discussion -- Appendix A A Brief Python Tutorial -- A.1 Overview -- A.2 Installing and Running Python -- A.3 Python Line Format -- A.4 Variables and Data Types -- A.5 Data Structures -- A.5.1 Strings -- A.5.2 Lists -- A.5.3 Tuples -- A.5.4 Sets -- A.5.5 Dictionaries -- A.6 Conditionals -- A.7 Iterations and Looping -- A.8 Generators and List Comprehensions -- A.9 Functions -- A.10 Objects and Classes -- A.11 Assignment, copy and deepcopy -- A.11.1 References -- A.11.2 Copying -- A.12 Modules -- A.13 Python Resources -- Bibliography -- Index. 410 0$aSpringer optimization and its applications ;$vVolume 67. 606 $aComputer simulation 606 $aMathematical optimization$xComputer simulation 606 $aPython (Computer program language) 606 $aSimulació per ordinador$2thub 606 $aOptimització matemàtica$2thub 606 $aPython (Llenguatge de programació)$2thub 608 $aLlibres electrònics$2thub 615 0$aComputer simulation. 615 0$aMathematical optimization$xComputer simulation. 615 0$aPython (Computer program language) 615 7$aSimulació per ordinador 615 7$aOptimització matemàtica 615 7$aPython (Llenguatge de programació) 676 $a003.3 700 $aBynum$b Michael L.$0849098 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466399003316 996 $aPyomo-optimization modeling in python$91896427 997 $aUNISA LEADER 03529nam 22007095 450 001 9910298280903321 005 20250609110107.0 010 $a1-4939-2556-3 024 7 $a10.1007/978-1-4939-2556-8 035 $a(CKB)3710000000402573 035 $a(EBL)2094440 035 $a(SSID)ssj0001500617 035 $a(PQKBManifestationID)11894608 035 $a(PQKBTitleCode)TC0001500617 035 $a(PQKBWorkID)11518472 035 $a(PQKB)10325408 035 $a(DE-He213)978-1-4939-2556-8 035 $a(MiAaPQ)EBC2094440 035 $a(PPN)185485561 035 $a(MiAaPQ)EBC3110136 035 $a(EXLCZ)993710000000402573 100 $a20150421d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in New Technology for Targeted Modification of Plant Genomes /$fedited by Feng Zhang, Holger Puchta, James G. Thomson 205 $a1st ed. 2015. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2015. 215 $a1 online resource (171 p.) 300 $aDescription based upon print version of record. 311 08$a1-4939-2555-5 320 $aIncludes bibliographical references and index. 327 $aDouble-strand break repair and its application to genome engineering in plants -- Engineering meganuclease for precise plant genome modification -- High efficient genome modification by designed Zinc Finger Nuclease -- Engineered TAL effector proteins:  versatile reagents for manipulating plant genomes -- Oligo-mediated targeted gene editing -- Gene targeting in crop species with effective selection systems -- Recombinase Technology for Precise Genome Engineering -- PBRM1: Developing CRISPR technology in major crop plants. 330 $aThis work provides an overview of the latest advances on precise genomic engineering technologies in plants. The research provided covers a wide range of topics, including recombinase and engineered nucleases-mediated targeted modification, negative/positive selection-based homologous recombination, and oligo nucleotide-mediated recombination. The text also discusses challenges and impacts of new technologies on present regulations for genetically modified organisms (GMOs). 606 $aPlant breeding 606 $aPlant genetics 606 $aPlant anatomy 606 $aPlants$xDevelopment 606 $aPlant Breeding/Biotechnology$3https://scigraph.springernature.com/ontologies/product-market-codes/L24060 606 $aPlant Genetics and Genomics$3https://scigraph.springernature.com/ontologies/product-market-codes/L32020 606 $aPlant Anatomy/Development$3https://scigraph.springernature.com/ontologies/product-market-codes/L24019 615 0$aPlant breeding. 615 0$aPlant genetics. 615 0$aPlant anatomy. 615 0$aPlants$xDevelopment. 615 14$aPlant Breeding/Biotechnology. 615 24$aPlant Genetics and Genomics. 615 24$aPlant Anatomy/Development. 676 $a570 676 $a571.32 676 $a581.35 676 $a631.52 676 $a660.6 702 $aZhang$b Feng$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPuchta$b Holger$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aThomson$b James G.$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910298280903321 996 $aAdvances in New Technology for Targeted Modification of Plant Genomes$92536136 997 $aUNINA