2026-04-17T03:01:50Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4737232024-11-04T07:19:39Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Juan, Ángel A. author Rabe, Markus author Ammouriova, Majsa author Panadero, Javier author Peidro, David author Riera Terrén, Daniel author 2023 In the field of logistics and transportation (L&T), this paper reviews the utilization of simheuristic algorithms to address NP-hard optimization problems under stochastic uncertainty. Then, the paper explores an extension of the simheuristics concept by introducing a fuzzy layer to tackle complex optimization problems involving both stochastic and fuzzy uncertainties. The hybrid approach combines simulation, metaheuristics, and fuzzy logic, offering a feasible methodology to solve large-scale NP-hard problems under general uncertainty scenarios. These scenarios are commonly encountered in L&T optimization challenges, such as the vehicle routing problem or the team orienteering problem, among many others. The proposed methodology allows for modeling various problem components-including travel times, service times, customers' demands, or the duration of electric batteries-as deterministic, stochastic, or fuzzy items. A cross-problem analysis of several computational experiments is conducted to validate the effectiveness of the fuzzy simheuristic methodology. Being a flexible methodology that allows us to tackle NP-hard challenges under general uncertainty scenarios, fuzzy simheuristics can also be applied in fields other than L&T. http://hdl.handle.net/2072/473723 Logistics and transportation Metaheuristics Simulation Fuzzy logic Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics