03963nam 2200625 450 991081645320332120200903223051.01-118-96648-11-118-96646-51-118-96647-3(CKB)3710000000187015(EBL)1734304(SSID)ssj0001340554(PQKBManifestationID)11739949(PQKBTitleCode)TC0001340554(PQKBWorkID)11381588(PQKB)10420201(OCoLC)883892138(MiAaPQ)EBC1734304(Au-PeEL)EBL1734304(CaPaEBR)ebr10892223(CaONFJC)MIL627080(PPN)192131524(EXLCZ)99371000000018701520140721h20142014 uy 0engur|n|---|||||txtccrMathematical programming solver based on local search /Frédéric Gardi [and four others]London, [England] ;Hoboken, New Jersey :ISTE :Wiley,2014.©20141 online resource (102 p.)Focus Computer Engineering Series,2051-249XDescription based upon print version of record.1-84821-686-6 Includes bibliographical references and index.Cover; Title Page; Copyright; Contents; Acknowledgments; Preface; Introduction; Chapter 1. Local Search: Methodology and Industrial Applications; 1.1. Our methodology: back to basics; 1.1.1. What are the needs in business and industry?; 1.1.2. The main ingredients of the recipe; 1.1.3. Enriching and enlarging neighborhoods; 1.1.4. High-performance software engineering; 1.2. Car sequencing for painting and assembly lines; 1.2.1. Search strategy and moves; 1.2.2. Enriching the moves and boosting their evaluation; 1.2.3. Experimental results and discussion1.3. Vehicle routing with inventory management1.3.1. State-of-the-art; 1.3.2. Search strategy and moves; 1.3.3. Incremental evaluation machinery; Chapter 2. Local Search for 0-1 Nonlinear Programming; 2.1. The LocalSolver project; 2.2. State-of-the-art; 2.3. Enriching modeling standards; 2.3.1. LocalSolver modeling formalism; 2.3.2. LocalSolver programming language; 2.4. The core algorithmic ideas; 2.4.1. Effective local search moves; 2.4.2. Incremental evaluation machinery; 2.5. Benchmarks; 2.5.1. Car sequencing; 2.5.2. Machine scheduling; 2.5.3. Quadratic assignment problem2.5.4. MIPLIB 2010Chapter 3. Toward an Optimization Solver Based on Neighborhood Search; 3.1. Using neighborhood search as global search strategy; 3.2. Extension to continuous and mixed optimization; 3.3. Separating the computation of solutions and bounds; 3.4. A new-generation, hybrid mathematical programming solver; Bibliography; Lists of Figures and Tables; Index This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kFocus series in computer engineering.Programming (Mathematics)Programming (Mathematics)519.7Gardi Frédéric1696346Gardi FrédéricMiAaPQMiAaPQMiAaPQBOOK9910816453203321Mathematical programming solver based on local search4076257UNINA