Mathematical programming solver based on local search / / Frédéric Gardi [and four others]

• Record Nr.: UNINA9910816453203321
• Autore: Gardi Frédéric
• Pubbl/distr/stampa: London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2014; ©2014
• ISBN: 1-118-96648-1; 1-118-96646-5; 1-118-96647-3
• Descrizione fisica: 1 online resource (102 p.)
• Collana: Focus Computer Engineering Series, , 2051-249X
• Disciplina: 519.7
• Soggetti: Programming (Mathematics)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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 discussion; 1.3. 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 problem; 2.5.4. 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
• Sommario/riassunto: 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 k