LEADER 03710nam 22006735 450 001 9910298526103321 005 20200920155655.0 010 $a3-642-41880-5 024 7 $a10.1007/978-3-642-41880-8 035 $a(CKB)3710000000085809 035 $a(EBL)1697766 035 $a(OCoLC)880132092 035 $a(SSID)ssj0001178985 035 $a(PQKBManifestationID)11692275 035 $a(PQKBTitleCode)TC0001178985 035 $a(PQKBWorkID)11169805 035 $a(PQKB)11600869 035 $a(MiAaPQ)EBC1697766 035 $a(DE-He213)978-3-642-41880-8 035 $a(PPN)176117083 035 $a(EXLCZ)993710000000085809 100 $a20140131d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultiagent Scheduling $eModels and Algorithms /$fby Alessandro Agnetis, Jean-Charles Billaut, Stanis?aw Gawiejnowicz, Dario Pacciarelli, Ameur Soukhal 205 $a1st ed. 2014. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2014. 215 $a1 online resource (281 p.) 300 $aDescription based upon print version of record. 311 $a3-642-41879-1 320 $aIncludes bibliographical references and index. 327 $a1. Multiagent Scheduling Fundamentals -- 2. Problems, Algorithms and Complexity -- 3. Single Machine Problems -- 4. Batching Scheduling Problems -- 5. Parallel Machine Scheduling Problems -- 6. Scheduling Problems with Variable Job Processing Times -- References. 330 $aScheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion. In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures. . 606 $aOperations research 606 $aDecision making 606 $aComputers 606 $aOperations Research/Decision Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/521000 606 $aModels and Principles$3https://scigraph.springernature.com/ontologies/product-market-codes/I18016 615 0$aOperations research. 615 0$aDecision making. 615 0$aComputers. 615 14$aOperations Research/Decision Theory. 615 24$aModels and Principles. 676 $a005.74 676 $a005.743 676 $a330 676 $a658.40301 700 $aAgnetis$b Alessandro$4aut$4http://id.loc.gov/vocabulary/relators/aut$08268 702 $aBillaut$b Jean-Charles$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aGawiejnowicz$b Stanis?aw$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aPacciarelli$b Dario$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSoukhal$b Ameur$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298526103321 996 $aMultiagent Scheduling$92495380 997 $aUNINA