This paper addresses the Capacitated Arc Routing Problem (CARP) using an Ant Colony Optimization scheme. Ant Colony schemes can compute solutions for medium scale instances of VRP. The proposed Ant Colony is dedicated to large-scale instances of CARP with more than 140 nodes and 190 arcs to service. The Ant Colony scheme is coupled with a local search procedure and provides high quality solutions. The benchmarks we carried out prove possible to obtain solutions as profitable as CARPET ones can be obtained using such scheme when a sufficient number of iterations is devoted to the ants. It competes with the Genetic Algorithm of Lacomme et al. regarding solution quality but it is more time consuming on large scale instances. The method has been intensively benchmarked on the well-known instances of Eglese, DeArmon and the last ones of Belenguer and Benavent. This research report is a step forward CARP resolution by Ant Colony proving ant schemes can compete with Taboo search methods and Genetic Algorithms
翻译:本文用Ant Colony Opptiminization (CARP) 方案处理能力弧路流问题。 Ant Colonony 方案可以计算中规模VRP的解决方案。 拟议的Ant Colonon 方案专门用于大型的CARP 方案, 共有140多个节点和190弧用于服务。 Ant Cononony 方案与当地搜索程序相结合, 并提供高质量的解决方案。 我们执行的基准证明, 利用这种方案可以获得与CARPET方案一样有利可图的解决方案。 它与Lacomme等人的遗传Algorithm 方案在解决方案质量上竞争, 但它在大型实例上花费的时间更多。 这种方法以众所周知的 Eglese、 DeArmon 和 Belenguer 和 Benavent 的最后一个实例为密集基准。 本研究报告是Ant CARP 方案向前迈出的一步, 证明 Ant Corony 方案可以与Tapoo搜索方法和遗传Algorithal Althms进行竞争。