| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 104 === The capacitated arc routing problem (CARP) is a special routing problem which has a variety of practical applications, such as snow plowing, street sweeping, winter gritting, household waste collection, The classical CARP is defined on an undirected graph with a set of edges. Each edge has a routing cost and a demand. The edges with positive demand make up the subset of the required edges. A set of identical vehicles with limited capacity is available. Each required edge has to be served exactly once by one vehicle. Each route must start and end at the depot. The objective of CARP is to find a set of vehicle routes to minimize the total cost.
Due to that CARP is a NP-hard problem, this research intends to present an Ant Colony Optimization (ACO) meta-heuristic to solve the CARP. The result is further improved by a local search with path-relinking for ACO. ACO is tested on eight groups of benchmark instances from the literature. The computational results show that ACO is effective to solve the CARP and its performance is highly competitive. ACO reaches 90% best known solutions in all instances.
In the practical application, this research applies the proposed ACO to solve the street cleaning planning problem with intermediate refill points in Kaohsiung city. The results are presented in a road network on the Google Map. The results show that the travel distance of street cleaning can be reduced by arranging and planning the new routes under our ACO algorithm. Finally, we hope that this research will add time windows and fuel costs constraints in the future.
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