LEADER 01395nam0-22004691--450- 001 990009451900403321 005 20150610155942.0 010 $a978-88-7192-554-7 035 $a000945190 035 $aFED01000945190 035 $a(Aleph)000945190FED01 035 $a000945190 100 $a20111014d2009----km-y0itay50------ba 101 1 $aita$ceng 102 $aIT 105 $aa-------001yy 200 1 $aElementi di ecologia$fThomas M. Smith, Robert Leo Smith$gedizione italiana a cura di Anna Occhipinti Ambrogi, Guido Baldino, Marco Cantonati 205 $a6. ed. 210 $aMilano$cPearson Benjamin Cummings$d2009 215 $aXX, 706 p.$cill.$d24 cm 454 0$12001$aElements of ecology$913800 610 0 $aEcologia 676 $a574.5$v20$zita 676 $a577$v21$zita 700 1$aSmith,$bThomas Michael$0305981 701 1$aSmith,$bRobert Leo$087612 702 1$aOcchipinti Ambrogi,$bAnna 702 1$aBaldino,$bGuido 702 1$aCantonati,$bMarco 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009451900403321 952 $a60 574.5 B 79$b13460$fFAGBC 952 $a577-SMI-2$b7095$fSC1 952 $a577-SMI-2A$b7096$fSC1 952 $a577-SMI-2B$b7097$fSC1 952 $aBL-577-10$b7153$fNAP10 959 $aFAGBC 959 $aSC1 959 $aNAP10 996 $aElements of ecology$913800 997 $aUNINA LEADER 05482nam 22006494a 450 001 9910143750403321 005 20170815111543.0 010 $a1-280-72221-5 010 $a9786610722211 010 $a0-470-30045-0 010 $a0-470-86735-3 010 $a0-470-86734-5 035 $a(CKB)1000000000356031 035 $a(EBL)281604 035 $a(OCoLC)476026849 035 $a(SSID)ssj0000131186 035 $a(PQKBManifestationID)11137213 035 $a(PQKBTitleCode)TC0000131186 035 $a(PQKBWorkID)10008104 035 $a(PQKB)11697310 035 $a(MiAaPQ)EBC281604 035 $a(PPN)223444766 035 $a(EXLCZ)991000000000356031 100 $a20060228d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCost optimization of structures$b[electronic resource] $efuzzy logic, genetic algorithms, and parallel computing /$fHojjat Adeli, Kamal C. Sarma 210 $aChichester, England ;$aHoboken, NJ $cWiley$dc2006 215 $a1 online resource (223 p.) 300 $aDescription based upon print version of record. 311 $a0-470-86733-7 320 $aIncludes bibliographical references (p. [185]-199) and index. 327 $aCost Optimization of Structures; Contents; Preface; Acknowledgments; About the Authors; 1 Introduction; 1.1 The Case for Cost Optimization; 1.2 Cost Optimization of Concrete Structures; 1.2.1 Concrete Beams and Slabs; 1.2.2 Concrete Columns; 1.2.3 Concrete Frame Structures; 1.2.4 Bridge Structures; 1.2.5 Water Tanks; 1.2.6 Folded Plates and Shear Walls; 1.2.7 Concrete Pipes; 1.2.8 Concrete Tensile Members; 1.2.9 Cost Optimization Using the Reliability Theory; 1.2.10 Concluding Comments; 1.3 Cost Optimization of Steel Structures; 1.3.1 Deterministic Cost Optimization 327 $a1.3.2 Cost Optimization Using the Reliability Theory1.3.3 Fuzzy Optimization; 1.3.4 Concluding Comments; 2 Evolutionary Computing and the Genetic Algorithm; 2.1 Overview and Basic Operations; 2.2 Coding and Decoding; 2.3 Basic Operations in Genetic Algorithms; 2.4 GA with the Penalty Function Method; 2.4.1 Problem Formulation for Axial Force (Truss) Structures; 2.4.2 Genetic Algorithm with the Penalty Function Method; 2.5 Augmented Lagrangian Method; 2.6 GA with the Augmented Lagrangian Method; 2.6.1 Problem Formulation for Axial Force (Truss) Structures 327 $a2.6.2 Genetic Algorithm with the Augmented Lagrangian Method3 Cost Optimization of Composite Floors; 3.1 Introduction; 3.2 Minimum Cost Design of Composite Beams; 3.2.1 Cost Function; 3.2.2 Constraints; 3.2.3 Problem Formulation as a Mixed Integer-Discrete Nonlinear Programming Problem; 3.3 Solution by the Floating-Point Genetic Algorithm; 3.3.1 Binary Versus Floating-Point GA; 3.3.2 Crossover Operation for the Floating-Point GA; 3.3.3 Mutation Operation for the Floating-Point GA; 3.3.4 Floating-Point GA for Cost Optimization of Composite Floors; 3.4 Solution by the Neural Dynamics Method 327 $a3.5 Counter Propagation Neural (CPN) Network for Function Approximations3.6 Examples; 3.6.1 Example 1; 3.6.2 Example 2; 4 Fuzzy Genetic Algorithm for Optimization of Steel Structures; 4.1 Introduction; 4.2 Fuzzy Set Theory and Structural Optimization; 4.3 Minimum Weight Design of Axially Loaded Space Structures; 4.4 Fuzzy Membership Functions; 4.5 Fuzzy Augmented Lagrangian Genetic Algorithm; 4.6 Implementation and Examples; 4.6.1 Example 1; 4.6.2 Example 2; 4.7 Conclusion; 5 Fuzzy Discrete Multi-criteria Cost Optimization of Steel Structures; 5.1 Cost of a Steel Structure 327 $a5.2 Primary Contributing Factors to the Cost of a Steel Structure5.3 Fuzzy Discrete Multi-criteria Cost Optimization; 5.4 Membership Functions; 5.4.1 Membership Function for Minimum Cost; 5.4.2 Membership Function for Minimum Weight; 5.4.3 Membership Function for Minimum Number of Section Types; 5.5 Fuzzy Membership Functions for Criteria with Unequal Importance; 5.6 Pareto Optimality; 5.7 Selection of Commercially Available Discrete Shapes; 5.8 Implementation and a Parametric Study; 5.9 Application to High-Rise Steel Structures; 5.9.1 Example 1; 5.9.2 Example 2; 5.10 Concluding Comments 327 $a6 Parallel Computing 330 $aWhile the weight of a structure constitutes a significant part of the cost, a minimum weight design is not necessarily the minimum cost design. Little attention in structural optimization has been paid to the cost optimization problem, particularly of realistic three-dimensional structures. Cost optimization is becoming a priority in all civil engineering projects, and the concept of Life-Cycle Costing is penetrating design, manufacturing and construction organizations. In this groundbreaking book the authors present novel computational models for cost optimization of large scale, realistic 606 $aStructural optimization$xMathematics 606 $aSkyscrapers$xDesign and construction$xCost control 615 0$aStructural optimization$xMathematics. 615 0$aSkyscrapers$xDesign and construction$xCost control. 676 $a620.00450151 676 $a721/.042 700 $aAdeli$b Hojjat$f1950-$0784299 701 $aSarma$b Kamal C$g(Kamal Chandra),$f1955-$0869607 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143750403321 996 $aCost optimization of structures$91941566 997 $aUNINA