LEADER 01178nam a22002771i 4500 001 991001369889707536 005 20031105125750.0 008 040407s1964 fr a||||||||||||||||fre 035 $ab12759776-39ule_inst 035 $aARCHE-073940$9ExL 040 $aDip.to Scienze Storiche$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a947 100 1 $aRambaud, Placide$034470 245 14$aLes transformations d'une société rurale :$bla Maurienne (1516-1962) /$cPlacide Rambaud et Monique Vincienne ; préface de Gabriel Le Bras 260 $aParis :$bColin,$c1964 300 $a280 p. :$bill. ;$c23 cm 440 0$aEtudes et memoires des centre d'études économiques ;$v59 651 4$aFrancia$xStoria 700 1 $aVincienne, Monique$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0245731 700 1 $aLe Bras, Gabriel 907 $a.b12759776$b02-04-14$c16-04-04 912 $a991001369889707536 945 $aLE009 STOR.71-49$g1$i2009000091047$lle009$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i13299797$z16-04-04 996 $aTransformations d'une société rurale$9956502 997 $aUNISALENTO 998 $ale009$b16-04-04$cm$da $e-$ffre$gfr $h4$i1 LEADER 04720nam 2200613 450 001 9910828951403321 005 20200520144314.0 010 $a1-119-13678-4 010 $a1-119-13676-8 010 $a1-119-13677-6 035 $a(CKB)3710000000596062 035 $a(EBL)4405837 035 $a(MiAaPQ)EBC4405837 035 $a(Au-PeEL)EBL4405837 035 $a(CaPaEBR)ebr11155983 035 $a(CaONFJC)MIL897664 035 $a(OCoLC)939864920 035 $a(PPN)242965024 035 $a(EXLCZ)993710000000596062 100 $a20160607h20162016 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aMetaheuristics for vehicle routing problems /$fNacima Labadie, Christian Prins, Caroline Prodhon 210 1$aLondon, England ;$aHoboken, New Jersey :$ciSTE :$cWiley,$d2016. 210 4$d©2016 215 $a1 online resource (197 p.) 225 0 $aComputer Engineering Series. Metaheuristics Set ;$vVolume 3 300 $aDescription based upon print version of record. 311 $a1-84821-811-7 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Copyright; Contents; Notations and Abbreviations; Notations; Abbreviations related to problems; Abbreviations related to methods; Introduction; Chapter 1. General Presentation of Vehicle Routing Problems; 1.1. Logistics management and combinatorial optimization; 1.1.1. History of logistics; 1.1.2. Logistics as a science; 1.1.3. Combinatorial optimization; 1.2. Vehicle routing problems; 1.2.1. Problems in transportation optimization; 1.2.2. Vehicle routing problems in other contexts; 1.2.3. Characteristics of vehicle routing problems; 1.2.3.1. Components 327 $a1.2.3.2. Constraints1.2.3.3. Objectives; 1.2.4. The capacitated vehicle routing problem; 1.2.4.1. Mathematical model; 1.2.4.2. Solution methods; 1.3. Conclusion; Chapter 2. Simple Heuristics and Local Search Procedures; 2.1. Simple heuristics; 2.1.1. Constructive heuristics; 2.1.2. Two-phase methods; 2.1.3. Best-of approach and randomization; 2.2. Local search; 2.2.1. Principle; 2.2.2. Classical moves; 2.2.3. Feasibility tests; 2.2.4. General approach from Vidal et al.; 2.2.5. Multiple neighborhoods; 2.2.6. Very constrained problems; 2.2.7. Acceleration techniques; 2.2.8. Complex moves 327 $a2.3. ConclusionChapter 3. Metaheuristics Generating a Sequence of Solutions; 3.1. Simulated annealing (SA); 3.1.1. Principle; 3.1.2. Simulated annealing in vehicle routing problems; 3.2. Greedy randomized adaptive search procedure: GRASP; 3.2.1. Principle; 3.2.2. GRASP in vehicle routing problems; 3.3. Tabu search; 3.3.1. Principle; 3.3.2. Tabu search in vehicle routing problems; 3.4. Variable neighborhood search; 3.4.1. Principle; 3.4.2. Variable neighborhood search in vehicle routing problems; 3.5. Iterated local search; 3.5.1. Principle 327 $a3.5.2. Iterated local search in vehicle routing problems3.6. Guided local search; 3.6.1. Principle; 3.6.2. Guided local search in vehicle routing problems; 3.7. Large neighborhood search; 3.7.1. Principle; 3.7.2. Large neighborhood search in vehicle routing problems; 3.8. Transitional forms; 3.8.1. Evolutionary local search principle; 3.8.2. Application to vehicle routing problems; 3.9. Selected examples; 3.9.1. GRASP for the location-routing problem; 3.9.2. Granular tabu search for the CVRP; 3.9.3. Adaptive large neighborhood search for the pickup and delivery problem with time windows 327 $a3.10. ConclusionChapter 4. Metaheuristics Based on a Set of Solutions; 4.1. Genetic algorithm and its variants; 4.1.1. Genetic algorithm; 4.1.2. Memetic algorithm; 4.1.3. Memetic algorithm with population management; 4.1.4. Genetic algorithm and its variants in vehicle routing problems; 4.2. Scatter search; 4.2.1. Scatter search principle; 4.2.2. Scatter search in vehicle routing problems; 4.3. Path relinking; 4.3.1. Principle; 4.3.2. Path relinking in vehicle routing problems; 4.4. Ant colony optimization; 4.4.1. Principle; 4.4.2. ACO in vehicle routing problems 327 $a4.5. Particle swarm optimization 606 $aTransportation problems (Programming) 606 $aMathematical optimization 615 0$aTransportation problems (Programming) 615 0$aMathematical optimization. 676 $a388.310285 700 $aLabadie$b Nacima$01685167 702 $aPrins$b Christian 702 $aProdhon$b Caroline 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828951403321 996 $aMetaheuristics for vehicle routing problems$94057072 997 $aUNINA