
Nature Inspired Optimisation for Delivery Problems by Neil Urquhart
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 outthe algorithms and techniques discussed.
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Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Deep Neural Evolution
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Lectures on Intelligent Systems
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Bioinspired Computation in Combinatorial Optimization
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Massively Parallel Evolutionary Computation on GPGPUs
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
Neil Urquhart is a lecturer in the School of Computing at Edinburgh Napier University. After qualifying in Computer Science he worked as a software developer and systems administrator. He returned to academia and completed a PhD in 2002 which examined the use of nature inspired techniques and software agents to construct and optimize delivery networks. Since 2002 he has worked as a lecturer at Edinburgh Napier where he is currently the program leader for Computing Science. His main research interests are algorithms, visualization, evolving systems, bioinspired computing, and modeling.
| SKU | Unavailable |
| ISBN 13 | 9783030981105 |
| ISBN 10 | 303098110X |
| Title | Nature Inspired Optimisation for Delivery Problems |
| Author | Neil Urquhart |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2023-05-16 |
| Number of pages | 259 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |




























