05375nam 2200697 a 450 991080934450332120240313144056.0978111860028311186002829781118600344111860034797811186001151118600118(CKB)2670000000336695(EBL)1124651(SSID)ssj0000904706(PQKBManifestationID)11476834(PQKBTitleCode)TC0000904706(PQKBWorkID)10921469(PQKB)11788453(Au-PeEL)EBL1124651(CaPaEBR)ebr10660627(CaONFJC)MIL527817(FINmELB)ELB178733(MiAaPQ)EBC1124651(OCoLC)828299271(Perlego)1013072(EXLCZ)99267000000033669520130222d2010 uy 0engur|n|---|||||txtccrApplications of combinatorial optimization /edited by Vangelis Th. Paschos1st ed.London ISTE ;Hoboken, N.J. Wiley20101 online resource (409 p.)Combinatorial optimization ;v. 3Description based upon print version of record.9781848211490 184821149X Cover; Applications of Combinatorial Optimization; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1. Airline Crew Pairing Optimization; 1.1. Introduction; 1.2. Definition of the problem; 1.2.1. Constructing subnetworks; 1.2.2. Pairing costs; 1.2.3. Model; 1.2.4. Case without resource constraints; 1.3. Solution approaches; 1.3.1. Decomposition principles; 1.3.2. Column generation, master problem and subproblem; 1.3.3. Branching methods for finding integer solutions; 1.4. Solving the subproblem for column generation; 1.4.1. Mathematical formulation1.4.2. General principle of effective label generation1.4.3. Case of one single resource: the bucket method; 1.4.4. Case of many resources: reduction of the resource space; 1.5. Conclusion; 1.6. Bibliography; Chapter 2. The Task Allocation Problem; 2.1. Presentation; 2.2. Definitions and modeling; 2.2.1. Definitions; 2.2.2. The processors; 2.2.3. Communications; 2.2.4. Tasks; 2.2.5. Allocation types; 2.2.6. Allocation/scheduling; 2.2.7. Modeling; 2.3. Review of the main works; 2.3.1. Polynomial cases; 2.3.2. Approximability; 2.3.3. Approximate solution; 2.3.4. Exact solution2.3.5. Independent tasks case2.4. A little-studied model; 2.4.1. Model; 2.4.2. A heuristic based on graphs; 2.5. Conclusion; 2.6. Bibliography; Chapter 3. A Comparison of Some Valid Inequality Generation Methods for General 0-1 Problems; 3.1. Introduction; 3.2. Presentation of the various techniques tested; 3.2.1. Exact separation with respect to a mixed relaxation; 3.2.2. Approximate separation using a heuristic; 3.2.3. Restriction + separation + relaxed lifting (RSRL); 3.2.4. Disjunctive programming and the lift and project procedure; 3.2.5. Reformulation-linearization technique (RLT)3.3. Computational results3.3.1. Presentation of test problems; 3.3.2. Presentation of the results; 3.3.3. Discussion of the computational results; 3.4. Bibliography; Chapter 4. Production Planning; 4.1. Introduction; 4.2. Hierarchical planning; 4.3. Strategic planning and productive system design; 4.3.1. Group technology; 4.3.2. Locating equipment; 4.4. Tactical planning and inventory management; 4.4.1. A linear programming model for medium-term planning; 4.4.2. Inventory management; 4.4.3. Wagner and Whitin model; 4.4.4. The economic order quantity model (EOQ)4.4.5. The EOQ model with joint replenishments4.5. Operations planning and scheduling; 4.5.1. Tooling; 4.5.2. Robotic cells; 4.6. Conclusion and perspectives; 4.7. Bibliography; Chapter 5. Operations Research and Goods Transportation; 5.1. Introduction; 5.2. Goods transport systems; 5.3. Systems design; 5.3.1. Location with balancing requirements; 5.3.2. Multiproduct production-distribution; 5.3.3. Hub location; 5.4. Long-distance transport; 5.4.1. Service network design; 5.4.2. Static formulations; 5.4.3. Dynamic formulations; 5.4.4. Fleet management; 5.5. Vehicle routing problems5.5.1. Definitions and complexityCombinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. "Applications of Combinatorial Optimization" is presenting a certain number among the most common and well-known applications of Combinatorial Optimization.ISTECombinatorial optimizationCombinatorial optimization.519.64Paschos Vangelis Th944252MiAaPQMiAaPQMiAaPQBOOK9910809344503321Applications of combinatorial optimization4017314UNINA02546nam 2200625Ia 450 991102004590332120200520144314.0978661275594197811180352141118035216978128275594912827559439780470612903047061290897804706128800470612886(CKB)2670000000035015(EBL)588828(SSID)ssj0000411025(PQKBManifestationID)11260758(PQKBTitleCode)TC0000411025(PQKBWorkID)10353997(PQKB)10107088(MiAaPQ)EBC588828(OCoLC)669165461(Perlego)1011920(EXLCZ)99267000000003501520091120d2010 uy 0engur|n|---|||||txtccrAdvanced process control beyond single loop control /Cecil L. SmithHoboken, N.J. Wileyc20101 online resource (464 p.)Description based upon print version of record.9780470381977 0470381973 Includes bibliographical references and index.ADVANCED PROCESS CONTROL; CONTENTS; Preface; 1 Introduction; 2 Cascade Control; 3 Split-Range Control; 4 Override Control; 5 Valve Position Control; 6 Ratio and Feedforward Control; 7 Loop Interaction; 8 Multivariable Control; IndexThis book fills the gap between basic control configurations (Practical Process Control) and model predictive control (MPC). For those loops whose performance has a direct impact on plant economics or product quality, going beyond simple feedback or cascade can improve control performance, or specifically, reduce the variance about the target. However, the effort required to implement such control technology must be offset by increased economic returns from production operations. The economic aspects of the application of the various advanced control technologies are stressed throughout the boChemical process controlChemical engineeringChemical process control.Chemical engineering.660/.2815Smith Cecil L209864MiAaPQMiAaPQMiAaPQBOOK9911020045903321Advanced process control1114713UNINA