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Decomposition for Large Scale Capacitated Arc Routing Problem

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If you have a question about this talk, please contact Leandro Minku.

Host: Prof. Xin Yao

Capacitated Arc Routing Problem (CARP) is a significant problem in the logistics area, which has a wide range of applications such as winter gritting, freight and post delivery. In practice, the problem is often large scale, which leads to a high difficulty to solve the problem effectively.

This talk discusses about such a scalability issue in Large-Scale CARP (LSCARP), and introduces an effective divide-and-conquer approach for solving LSCARP . The proposed approach adopts the Cooperative Co-evolution (CC) framework to decompose it into smaller ones and solve them separately. An effective decomposition scheme called the Route Distance Grouping (RDG) is developed to decompose the problem. Its merit is twofold: Firstly, it employs the route information of the best-so-far solution, so that the quality of the decomposition is upper bounded by that of the best-so-far solution. Thus, it can keep improving the decomposition by updating the best-so-far solution during the search. Secondly, it defines a distance between routes, based on which the potentially better decompositions can be identified. Therefore, RDG is able to obtain promising decompositions and focus the search on the promising regions of the vast solution space.

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This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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