LEADER 05201nam 2200613 a 450 001 9910141601303321 005 20230725035313.0 010 $a1-118-60028-2 010 $a1-118-60034-7 010 $a1-118-60011-8 035 $a(CKB)2670000000336695 035 $a(EBL)1124651 035 $a(OCoLC)828299271 035 $a(SSID)ssj0000904706 035 $a(PQKBManifestationID)11476834 035 $a(PQKBTitleCode)TC0000904706 035 $a(PQKBWorkID)10921469 035 $a(PQKB)11788453 035 $a(MiAaPQ)EBC1124651 035 $a(Au-PeEL)EBL1124651 035 $a(CaPaEBR)ebr10660627 035 $a(CaONFJC)MIL527817 035 $a(EXLCZ)992670000000336695 100 $a20130222d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aApplications of combinatorial optimization$b[electronic resource] /$fedited by Vangelis Th. Paschos 210 $aLondon $cISTE ;$aHoboken, N.J. $cWiley$d2010 215 $a1 online resource (409 p.) 225 0$aCombinatorial optimization ;$vv. 3 300 $aDescription based upon print version of record. 311 $a1-84821-149-X 327 $aCover; 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 formulation 327 $a1.4.2. 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 solution 327 $a2.3.5. 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) 327 $a3.3. 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) 327 $a4.4.5. 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 problems 327 $a5.5.1. Definitions and complexity 330 $aCombinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. "Applications of Combinatorial Optimization" is presenting a certain number among the most common and well-known applications of Combinatorial Optimization. 410 0$aISTE 606 $aCombinatorial optimization 615 0$aCombinatorial optimization. 676 $a519.64 701 $aPaschos$b Vangelis Th$0944252 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141601303321 996 $aApplications of combinatorial optimization$92165719 997 $aUNINA