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RT Book, Whole SR Electronic DC OPAC T1 Nature Inspired Optimisation for Delivery Problems : From Theory to the Real World / by Neil Urquhart T2 Natural Computing Series. ISSN:26276461 A1 Urquhart, Neil A1 SpringerLink (Online service) YR 2022 FD 2022 SP XVII, 259 p. 75 illus., 43 illus. in color K1 Computer science K1 Computational intelligence K1 Artificial intelligence K1 Operations research K1 Mathematical optimization K1 Theory of Computation K1 Computational Intelligence K1 Artificial Intelligence K1 Operations Research and Decision Theory K1 Optimization ED 1st ed. 2022. PB Springer International Publishing : Imprint: Springer PP Cham SN 9783030981082 LA English (英語) CL LCC:QA75.5-76.95 CL DC23:004.0151 NO Part I, Simple Yet Complex Problems -- The Traveling Salesman Problem -- Vehicle Routing Problems (VRPs) -- More Complex VRPs -- Multi-objective Problems -- Part II, Data and Routing -- An Introduction to Geospatial Data -- Routing Algorithms -- Linking to Data Sources -- Visualising Data -- Part III, Real-World Problems -- Food Deliveries in Rural Areas -- Delivering Milk -- Postal Deliveries -- Mobile Workforce Routing -- Urban Logistics NO This book explains classic routing and transportation problems and solutions, before offering insights based on successful real-world solutions. The chapters in Part I introduce and explain the traveling salesperson problem (TSP), vehicle routing problems (VRPs), and multi-objective problems, with an emphasis on heuristic approaches and software engineering aspects. In turn, Part II demonstrates how to exploit geospatial data, routing algorithms, and visualization. In Part III, the above techniques and insights are combined in real-world success stories from domains such as food delivery in rural areas, postal delivery, workforce routing, and urban logistics. The book offers a valuable supporting text for advanced undergraduate and graduate courses and projects in Computer Science, Engineering, Operations Research, and Mathematics. It is accompanied by a repository of source code, allowing readers to try out the algorithms and techniques discussed NO HTTP:URL=https://doi.org/10.1007/978-3-030-98108-2 NO 書誌ID=EB00001632; LK [E Book]https://doi.org/10.1007/978-3-030-98108-2 OL 30