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Vehicle Routing through Simulation of Natural Processes
| Content Provider | Scilit |
|---|---|
| Author | Potvin, Jean-Yves Thangiah, Sam R. |
| Copyright Year | 2020 |
| Description | 142 143Vehicle routing problems hold a central place in distribution management. Their economic importance has motivated both academic researchers and private companies to find ways to efficiently perform the transportation of goods and services. A vehicle routing problem requires the allocation of each customer to a particular vehicle and the ordering of these customers on each route to minimize the transportation costs, subject to various constraints such as vehicle capacity and route time duration. In this chapter, we review recent attempts at solving those problems, using methods motivated by natural processes, like genetic algorithms and neural networks. Book Name: Fusion of Neural Networks, Fuzzy Systems, and Genetic Algorithms |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2006-0-06203-3&isbn=9780367811464&doi=10.1201/9780367811464-6&format=pdf |
| Ending Page | 168 |
| Page Count | 28 |
| Starting Page | 141 |
| DOI | 10.1201/9780367811464-6 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-01-29 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Fusion of Neural Networks, Fuzzy Systems, and Genetic Algorithms Transplantation Algorithms and Neural Networks |
| Content Type | Text |
| Resource Type | Chapter |
