LEADER 05715nam 2200781 a 450 001 9910141493603321 005 20200520144314.0 010 $a1-118-57789-2 010 $a1-299-14153-6 010 $a1-118-57775-2 010 $a1-118-57784-1 035 $a(CKB)2670000000327413 035 $a(EBL)1117270 035 $a(OCoLC)827208481 035 $a(SSID)ssj0000884299 035 $a(PQKBManifestationID)11499521 035 $a(PQKBTitleCode)TC0000884299 035 $a(PQKBWorkID)10940505 035 $a(PQKB)10348247 035 $a(OCoLC)828735208 035 $a(MiAaPQ)EBC1117270 035 $a(Au-PeEL)EBL1117270 035 $a(CaPaEBR)ebr10653871 035 $a(CaONFJC)MIL445403 035 $a(PPN)185427782 035 $a(EXLCZ)992670000000327413 100 $a20120905d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOptimization in engineering sciences$b[electronic resource] $eexact methods /$fPierre Borne ... [et al.] 210 $aHoboken, N.J. $cISTE Ltd/John Wiley and Sons Inc.$d2013 215 $a1 online resource (328 p.) 225 1 $aISTE 300 $aDescription based upon print version of record. 311 $a1-84821-432-4 320 $aIncludes bibliographical references and index. 327 $aTitle Page; Contents; Foreword; Preface; List of Acronyms; Chapter 1. Linear Programming; 1.1. Objective of linear programming; 1.2. Stating the problem; 1.3. Lagrange method; 1.4. Simplex algorithm; 1.4.1. Principle; 1.4.2. Simplicial form formulation; 1.4.3. Transition from one simplicial form to another; 1.4.4. Summary of the simplex algorithm; 1.5. Implementation example; 1.6. Linear programming applied to the optimization of resource allocation; 1.6.1. Areas of application; 1.6.2. Resource allocation for advertising; 1.6.3. Optimization of a cut of paper rolls 327 $a1.6.4. Structure of linear program of an optimal control problemChapter 2. Nonlinear Programming; 2.1. Problem formulation; 2.2. Karush-Kuhn-Tucker conditions; 2.3. General search algorithm; 2.3.1. Main steps; 2.3.2. Computing the search direction; 2.3.3. Computation of advancement step; 2.4. Monovariable methods; 2.4.1. Coggin's method (of polynomial interpolation); 2.4.2. Golden section method; 2.5. Multivariable methods; 2.5.1. Direct search methods; 2.5.2. Gradient methods; Chapter 3. Dynamic Programming; 3.1. Principle of dynamic programming; 3.1.1. Stating the problem 327 $a3.1.2. Decision problem3.2. Recurrence equation of optimality; 3.3. Particular cases; 3.3.1. Infinite horizon stationary problems; 3.3.2. Variable horizon problem; 3.3.3. Random horizon problem; 3.3.4. Taking into account sum-like constraints; 3.3.5. Random evolution law; 3.3.6. Initialization when the final state is imposed; 3.3.7. The case when the necessary information is not always available; 3.4. Examples; 3.4.1. Route optimization; 3.4.2. The smuggler problem; Chapter 4. Hopfield Networks; 4.1. Structure; 4.2. Continuous dynamic Hopfield networks; 4.2.1. General problem 327 $a4.2.2. Application to the traveling salesman problem4.3. Optimization by Hopfield networks, based on simulated annealing; 4.3.1. Deterministic method; 4.3.2. Stochastic method; Chapter 5. Optimization in System Identification; 5.1. The optimal identification principle; 5.2. Formulation of optimal identification problems; 5.2.1. General problem; 5.2.2. Formulation based on optimization theory; 5.2.3. Formulation based on estimation theory (statistics); 5.3. Usual identification models; 5.3.1. General model; 5.3.2. Rational input/output (RIO) models 327 $a5.3.3. Class of autoregressive models (ARMAX)5.3.4. Class of state space representation models; 5.4. Basic least squares method; 5.4.1. LSM type solution; 5.4.2. Geometric interpretation of the LSM solution; 5.4.3. Consistency of the LSM type solution; 5.4.4. Example of application of the LSM for an ARX model; 5.5. Modified least squares methods; 5.5.1. Recovering lost consistency; 5.5.2. Extended LSM; 5.5.3. Instrumental variables method; 5.6. Minimum prediction error method; 5.6.1. Basic principle and algorithm; 5.6.2. Implementation of the MPEM for ARMAX models 327 $a5.6.3. Convergence and consistency of MPEM type estimations 330 $a The purpose of this book is to present the main methods of static and dynamic optimization. It has been written within the framework of the European Union project - ERRIC (Empowering Romanian Research on Intelligent Information Technologies), funded by the EU's FP7 Research Potential program and developed in cooperation between French and Romanian teaching researchers.Through the principles of various proposed algorithms (with additional references) this book allows the interested reader to explore various methods of implementation such as linear programming, nonlinear programming - p 410 0$aISTE 606 $aEngineering mathematics 606 $aMathematical optimization 606 $aProgram transformation (Computer programming) 606 $aAlgorithms 606 $aSystems engineering 615 0$aEngineering mathematics. 615 0$aMathematical optimization. 615 0$aProgram transformation (Computer programming) 615 0$aAlgorithms. 615 0$aSystems engineering. 676 $a519.92 676 $a629.89 700 $aBorne$b Pierre$060243 701 $aBorne$b Pierre$060243 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141493603321 996 $aOptimization in engineering sciences$92096768 997 $aUNINA