000 03816nam a22004575i 4500
001 978-0-387-23485-4
003 DE-He213
005 20250710083928.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387234854
_a99780387234854
024 7 _a10.1007/0-387-23485-3
_2doi
082 0 4 _a003.3
_223
100 1 _aKallrath, Julia.
_eauthor.
245 1 0 _aOnline Storage Systems and Transportation Problems with Applications
_h[recurso electrónico] :
_bOptimization Models and Mathematical Solutions /
_cby Julia Kallrath.
264 1 _aBoston, MA :
_bSpringer US,
_c2005.
300 _aXIV, 222 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aApplied Optimization,
_x1384-6485 ;
_v91
505 0 _aBatch Presorting Problems. I Models and Solution Approaches -- Batch Presorting Problems. II Applications in Inventory Logistics -- Vehicle Routing Problems in Hospital Transportation. I Models and Solution Approaches -- Vehicle Routing Problems in Hospital Transportation. II Applications and Case Studies -- Summary.
520 _aThis books covers the analysis and development of online algorithms involving exact optimization and heuristic techniques, and their application to solve two real life problems. The first problem is concerned with a complex technical system: a special carousel based high-speed storage system - Rotastore. It is shown that this logistic problem leads to an NP-hard Batch PreSorting problem which is not easy to solve optimally in offline situations. The author considered a polynomial case and developed an exact algorithm for offline situations. Competitive analysis showed that the proposed online algorithm is 3/2-competitive. Online algorithms with lookahead, improve the online solutions in particular cases. If the capacity constraint on additional storage is neglected the problem has a totally unimodular polyhedron. The second problem originates in the health sector and leads to a vehicle routing problem. Reasonable solutions for the offline case covering a whole day with a few hundred orders are constructed with a heuristic approach, as well as by simulated annealing. Optimal solutions for typical online instances are computed by an efficient column enumeration approach leading to a set partitioning problem and a set of routing-scheduling subproblems. The latter are solved exactly with a branch-and-bound method which prunes nodes if they are value-dominated by previous found solutions or if they are infeasible with respect to the capacity or temporal constraints. The branch-and-bound method developed is suitable to solve any kind of sequencing-scheduling problem involving accumulative objective functions and constraints, which can be evaluated sequentially. The column enumeration approach the author has developed to solve this hospital problem is of general nature and thus can be embedded into any decision-support system involving assigning, sequencing and scheduling.
650 0 _aMATHEMATICS.
650 0 _aALGORITHMS.
650 0 _aMATHEMATICAL OPTIMIZATION.
650 1 4 _aMATHEMATICS.
650 2 4 _aMATHEMATICAL MODELING AND INDUSTRIAL MATHEMATICS.
650 2 4 _aOPTIMIZATION.
650 2 4 _aAPPLICATIONS OF MATHEMATICS.
650 2 4 _aALGORITHMS.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781402029714
830 0 _aApplied Optimization,
_x1384-6485 ;
_v91
856 4 0 _uhttp://dx.doi.org/10.1007/0-387-23485-3
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-SMA
942 _2ddc
_cER
999 _c56217
_d56217