The Vehicle Routing Problem has been a popular research topic in logistics (Physical distribution) which is of much practical value. This thesis studies has the research technique toward vehicle routing problem and the advantage that the immune algorithm has over other algorithms. It also puts forward the method of solving vehicle routing problem by the immune algorithm. In the solution procedure, this thesis creates a new encoded model which can increase the operational efficiency of the algorithm presented by decreasing the encoding length. Through the design of immune memory data and the accelerating or restraining mechanism of the density between the antibodies, this algorithm enables the multiformity of the solution, avoids convergence to partial optimal solution and at the same time effectively avoids the optimal solution in the process of evolution. The experimental result shows that this algorithm is one effective algorithm solving the problem of vehicle routing which makes it possible to get the optimal solution fast.
| Identifer | oai:union.ndltd.org:Quebec/oai:constellation.uqac.ca:145 |
| Date | January 2009 |
| Creators | Xu, Jiangang |
| Source Sets | Université du Québec à Chicoutimi |
| Language | English |
| Detected Language | English |
| Type | Thèse ou mémoire de l'UQAC, NonPeerReviewed |
| Format | application/pdf |
| Relation | http://constellation.uqac.ca/145/, doi:10.1522/030118613 |
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