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000726444 020__ $$a9783319150338$$qelectronic book
000726444 020__ $$a3319150332$$qelectronic book
000726444 020__ $$z9783319150321
000726444 0247_ $$a10.1007/978-3-319-15033-8$$2doi
000726444 035__ $$aSP(OCoLC)ocn906804055
000726444 035__ $$aSP(OCoLC)906804055
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000726444 049__ $$aISEA
000726444 050_4 $$aT57.62
000726444 08204 $$a003.3$$223
000726444 24500 $$aApplied simulation and optimization$$h[electronic resource] :$$bin logistics, industrial and aeronautical practice /$$cMiguel Mujica Mota, Idalia Flores de la Mota, Daniel Guimarans Serrano, editors.
000726444 264_1 $$aCham :$$bSpringer,$$c[2015]
000726444 300__ $$a1 online resource :$$bcolor illustrations
000726444 336__ $$atext$$btxt$$2rdacontent
000726444 337__ $$acomputer$$bc$$2rdamedia
000726444 338__ $$aonline resource$$bcr$$2rdacarrier
000726444 504__ $$aIncludes bibliographical references.
000726444 5050_ $$aSimulation-based Optimization with HeuristicLab: Practical Guidelines and Real World Applications -- Simulation Optimization Approach to solve a complex multiobjective redundancy allocation problem -- OR AND SIMULATION IN COMBINATION FOR OPTIMIZATION -- Tree Search and Simulation -- Integrated solutions for delivery planning and scheduling in distribution centres -- Large Neighbourhood Search and Simulation for Disruption Management in the Airline Industry -- Allocation of Airport check?in counters using a Simulation?Optimization Approach -- Simulation and Optimization of the Pre-hospital Care System of the National University of Mexico -- Simulation Based Optimization Using Greedy Techniques and Simulated Annealing for Optimal Equipment Selection within Print Production Environments -- Linear Bus Holding Model for Real Time Traffic Network Control.
000726444 506__ $$aAccess limited to authorized users.
000726444 520__ $$aPresenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulation?s flexibility with optimization techniques? robustness. Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.
000726444 588__ $$aOnline resource; title from PDF title page (viewed April 9, 2015).
000726444 650_0 $$aSimulation methods.
000726444 650_0 $$aMathematical optimization.
000726444 650_0 $$aStochastic processes.
000726444 7001_ $$aMujica Mota, Miguel,$$eeditor.
000726444 7001_ $$aMota, Idalia Flores de la,$$eeditor.
000726444 7001_ $$aGuimarans Serrano, Daniel,$$eeditor.
000726444 77608 $$iPrint version:$$tApplied simulation and optimization : in logistics, industrial and aeronautical practice.$$dCham, Switzerland : Springer, c2015$$z9783319150321
000726444 852__ $$bebk
000726444 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-15033-8$$zOnline Access$$91397441.1
000726444 909CO $$ooai:library.usi.edu:726444$$pGLOBAL_SET
000726444 980__ $$aEBOOK
000726444 980__ $$aBIB
000726444 982__ $$aEbook
000726444 983__ $$aOnline
000726444 994__ $$a92$$bISE