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Applied Simulation and Optimization electronic resource In Logistics, Industrial and Aeronautical Practice / edited by Miguel Mujica Mota, Idalia Flores De La Mota, Daniel Guimarans Serrano.

Contributor(s): Mujica Mota, Miguel [editor.] | De La Mota, Idalia Flores [editor.] | Guimarans Serrano, Daniel [editor.] | SpringerLink (Online service)Material type: TextTextPublication details: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XV, 319 p. 138 illus., 80 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319150338Subject(s): mathematics | Computer simulation | Computer mathematics | Applied mathematics | Engineering mathematics | Industrial engineering | Production engineering | Mathematics | Computational Science and Engineering | Appl.Mathematics/Computational Methods of Engineering | Simulation and Modeling | Industrial and Production EngineeringDDC classification: 004 LOC classification: QA71-90Online resources: Click here to access online
Contents:
Simulation-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.
In: Springer eBooksSummary: Presenting 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.
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Simulation-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.

Presenting 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.

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