LEADER 03663nam  22006255  450 
001 9910592992703321
005 20251113211444.0
010   $a9789811942150$b(electronic bk.)
010   $z9789811942143
024 7 $a10.1007/978-981-19-4215-0
035   $a(MiAaPQ)EBC7084544
035   $a(Au-PeEL)EBL7084544
035   $a(CKB)24819673500041
035   $a(PPN)264958128
035   $a(OCoLC)1344346980
035   $a(DE-He213)978-981-19-4215-0
035   $a(EXLCZ)9924819673500041
100   $a20220910d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAssembly Line Balancing under Uncertain Task Time and Demand Volatility /$fby Yuchen Li
205   $a1st ed. 2022.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022.
215   $a1 online resource (164 pages)
225 1 $aEngineering Applications of Computational Methods,$x2662-3374 ;$v8
311 08$aPrint version: Li, Yuchen Assembly Line Balancing under Uncertain Task Time and Demand Volatility Singapore : Springer,c2022 9789811942143 
320   $aIncludes bibliographical references.
327   $aPreface -- Chapter 1 Introduction -- Chapter 2 State of the art -- Chapter 3 Rebalancing an assembly line with disruptions -- Chapter 4 Two-sided assembly line balancing under uncertain task time attributes -- Chapter 5 System reliability optimization under uncertain task time attributes -- Chapter 6 Assembly line balancing under task learning and uncertain demand -- Chapter 7 A joint assembly line balancing and lot-sizing problem under uncertain demand -- References.
330   $aThis book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
410  0$aEngineering Applications of Computational Methods,$x2662-3374 ;$v8
606   $aIndustrial engineering
606   $aProduction engineering
606   $aMathematical models
606   $aMathematical optimization
606   $aIndustrial and Production Engineering
606   $aMathematical Modeling and Industrial Mathematics
606   $aOptimization
615  0$aIndustrial engineering.
615  0$aProduction engineering.
615  0$aMathematical models.
615  0$aMathematical optimization.
615 14$aIndustrial and Production Engineering.
615 24$aMathematical Modeling and Industrial Mathematics.
615 24$aOptimization.
676   $a670.427
700   $aLi$b Yuchen$01257648
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910592992703321
996   $aAssembly Line Balancing under Uncertain Task Time and Demand Volatility$92914330
997   $aUNINA