LEADER 06416nam 2200577 450 001 996466407603316 005 20230619190008.0 010 $a3-030-83442-5 035 $a(CKB)5470000001298869 035 $a(MiAaPQ)EBC6796401 035 $a(Au-PeEL)EBL6796401 035 $a(OCoLC)1281772391 035 $a(PPN)258298448 035 $a(EXLCZ)995470000001298869 100 $a20220721d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMathematical control and numerical applications $eJANO13, Khouribga, Morocco, February 22-24, 2021 /$fAbdeljalil Nachaoui, Abdelilah Hakim, Amine Laghrib, editors 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (168 pages) 225 1 $aSpringer Proceedings in Mathematics & Statistics ;$vVolume 372 311 $a3-030-83441-7 327 $aIntro -- Preface -- Contents -- VRP with Flexible Time Windows Using the ALNS Metaheuristic Algorithm -- 1 Problem Formulation of the VRPFlexTW -- 2 ALNS State of the Art in the Context of VRP -- 3 ALNS Techniques for VRPFlexTW -- 4 Numerical Experiment -- 5 Conclusion -- References -- VRPTW: From Mathematical Models to Computing Science Tools -- 1 Introduction -- 2 Mathematical Formulation -- 3 Adaptive Large Neighborhood Search -- 4 Deterministic Vehicle Routing Problem with Time Windows (VRPTW) -- 4.1 The Modified Adaptive Large Neighborhood Search (MALNS) -- 4.2 The Multi-threading Parallel ALNS -- 5 Robust Vehicle Routing Problem with Time Windows (RVRPTW) -- 5.1 Sequential Approach to Solve the RVRPTW -- 5.2 Multi-threading Parallel Approach to Solve the RVRPTW -- 6 Computational Experiments -- 6.1 Computational Results of the MALNS -- 6.2 Computational Results of the Multi-threading Parallel ALNS -- 6.3 Computational Results of the Sequential Robust Approach -- 6.4 Computational Results of the Parallel Robust Approaches -- 7 Conclusion -- References -- An Anisotropic PDE for Multi-frame Super-Resolution Image Reconstruction -- 1 Multi-frame SR Model -- 2 Discritization and Numerical Result -- References -- Acceleration of the KMF Algorithm Convergence to Solve the Cauchy Problem for Poisson's Equation -- 1 Introduction -- 2 Cauchy Problem for Poisson's Equation and JN Relaxed Algorithm -- 2.1 The JN Relaxed Algorithm -- 3 Convergence Analysis -- 4 Acceleration of Convergence -- 5 Numerical Results -- 6 Conclusion -- References -- Identification of Genuine from Fake Banknotes Using an Enhanced Machine Learning Approach -- 1 Introduction -- 2 Formulating the Binary Classification Problem -- 2.1 Kernel Function -- 3 Hinge Loss Function -- 4 Experimental Results -- 4.1 Feature Importance -- 5 Conclusion -- References. 327 $aIdentification of Robin Coefficient in Elliptic Problem by a Coupled Complex Boundary Method -- 1 Introduction -- 2 A Reformulation with CCBM -- 3 Tikhonov Regularization -- 4 Numerical Results -- 4.1 Identification Results Without Noise -- 4.2 Identification Results with Noise -- References -- A New Space-Variant Optimization Approach for Image Segmentation -- 1 Introduction -- 2 The Problem Formulation -- 3 The ADMM Algorithm -- 4 Numerical Results -- 5 Conclusion -- References -- A Lagrangian Mixed Finite Elements Method for Advection-Diffusion Equations -- 1 Introduction -- 2 Eulerian-Lagrangian Method -- 2.1 Lagrangian Discretization of the Advection Problem -- 2.2 Eulerian Discretization of the Diffusion Subproblem -- 2.3 Particle-Mesh Interaction -- 2.4 Mesh-Particle Projection -- 3 Numerical Experiments -- References -- Adaptation by Nash Games in Gradient-Based Multi-objective/Multi-disciplinary Optimization -- 1 Introduction -- 2 Nash-Game-Based Adaptation Algorithm -- 2.1 Mathematical Problem Definition -- 2.2 Convex Hull, Common Descent Direction and Directional Derivatives -- 2.3 Preliminary Calculations -- 2.4 Nash Game Formulation and Statement of Theoretical Result -- 3 Proof and Convergence Rate -- 3.1 Compatibility -- 3.2 Continuum of Nash Equilibria -- 3.3 Variation of the Primary Cost Functions Along the Continuum -- 3.4 Variation of the Secondary Cost Functions Along the Continuum -- 3.5 Secondary Cost Functions -- 4 Illustration of the Prioritized Multi-objective Optimization Approach -- 4.1 Numerical Implementation -- 4.2 Application to the Sizing of a Sandwich Element for Optimal Mechanical Resistance -- 5 Conclusion and Perspective -- References -- Blind Noisy Mixture Separation for Dependent Sources -- 1 Introduction -- 2 Problem Statement -- 3 First Step: Denoising of Observations -- 3.1 Regularization Total Variation. 327 $a3.2 Discretization -- 3.3 Algorithme de Projection de Chambolle -- 4 Second Step: BSS Based on the Combination of Copula and TV -- 4.1 Case of Independent Sources -- 4.2 Case of Dependent Sources -- 5 Simulation Results -- 6 Conclusion -- References -- Blind Separation of Dependent Sources Using Copula -- 1 Introduction -- 2 Problem Statement -- 3 Copula -- 4 Case of Independent Sources -- 5 Case of Dependent Sources -- 5.1 Procedure 1: Dependent BSS Based on a Priori Knowledge on the Sources -- 5.2 Procedure 2: BSS for Dependent Sources When the Dependency Model Is Known and the Parameter Is Unknown -- 5.3 Procedure 3: BSS for Dependent Sources When the Dependency Model Is Unknown and the Parameter Is Unknown -- 6 Experimental Performance Study -- 6.1 Series 1: Tests with Various Types of Signals -- 6.2 Series 2: Tests with Images -- 7 Conclusion -- References. 410 0$aSpringer proceedings in mathematics & statistics ;$vVolume 372. 606 $aNumerical analysis$vCongresses 606 $aComputer science$xMathematics$vCongresses 606 $aAnàlisi numèrica$2thub 606 $aInformàtica$2thub 608 $aCongressos$2thub 608 $aLlibres electrònics$2thub 615 0$aNumerical analysis 615 0$aComputer science$xMathematics 615 7$aAnàlisi numèrica 615 7$aInformàtica 676 $a519.4 702 $aNachaoui$b Abdeljalil 702 $aHakim$b Abdelilah 702 $aLaghrib$b Amine 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466407603316 996 $aMathematical control and numerical applications$92901142 997 $aUNISA