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Title: | Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty |
Author: | Tordecilla, Rafael D. do Carmo Martins, Leandro Panadero Martínez, Javier Copado Mendez, Pedro Jesus Pérez Bernabeu, Elena Juan, Angel A. |
Others: | Universitat Oberta de Catalunya (UOC) Internet Interdisciplinary Institute (IN3) |
Citation: | Tordecilla, R.D.; Martins, L.d.C.; Panadero, J.; Copado, P.J.; Perez-Bernabeu, E.; Juan, A.A. Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty. Appl. Sci. 2021, 11, 7950. https://doi.org/10.3390/app11177950 |
Abstract: | In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems with both stochastic and fuzzy uncertainty. This hybrid approach combines simulation, metaheuristics, and fuzzy logic to generate near-optimal solutions to large scale NP-hard problems that typically arise in many transportation activities, including the vehicle routing problem, the arc routing problem, or the team orienteering problem. The methodology allows us to model different components-such as travel times, service times, or customers' demands-as deterministic, stochastic, or fuzzy. A series of computational experiments contribute to validate our hybrid approach, which can also be extended to other optimization problems in areas such as manufacturing and production, smart cities, telecommunication networks, etc. |
Keywords: | transportation vehicle routing problems metaheuristics simulation-optimization fuzzy techniques |
DOI: | https://doi.org/10.3390/app11177950 |
Document type: | info:eu-repo/semantics/article |
Issue Date: | 2-Sep-2021 |
Publication license: | http://creativecommons.org/licenses/by/3.0/es/ |
Appears in Collections: | Articles cientÍfics Articles |
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