Solving Dynamic Delivery Services Using Ant Colony Optimization

• Autor(a) principal: Martins, M.
• Data de Publicação: 2020
• Outros Autores: Coito, T., Firme, B., Viegas, J., Sousa, J., Figueiredo, Joao, Vieira, S.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/28812; https://doi.org/MARTINS, M., COITO, T., FIRME, B., VIEGAS, J., SOUSA, J., FIGUEIREDO, J., VIEIRA, S. [2020] “Solving Dynamic Delivery Services Using Ant Colony Optimization”. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, https://doi.org/10.1007/978-3-030-50146-4_25; https://doi.org/10.1007/978-3-030-50146-4_25
• topic: Pickup delivery problem; Ant Colony Optimization; Local Search; Time windows; Dynamic requests

This article presents a model for courier services designed to guide a fleet of vehicles over a dynamic set of requests. Motivation for this problem comes from a real-world scenario in an ever-changing environment, where the time to solve such optimization problem is constrained instead of endlessly searching for the optimal solution. First, a hybrid method combining Ant Colony Optimization with Local Search is proposed, which is used to solve a given static instance. Then, a framework to handle and adapt to dynamic changes over time is defined. A new method pairing nearest neighbourhood search with subtractive clustering is proposed to improve initial solutions and accelerate the convergence of the optimization algorithm. Overall, the proposed strategy presents good results for the dynamic environment and is suitable to be applied on real-world scenarios.