Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics
Juan, Ángel A. (Universitat Politècnica de València)
Rabe, Markus (TU Dortmund University. Department of IT in Production and Logistics)
Ammouriova, Majsa (Universitat Oberta de Catalunya. Departament d'Informàtica)
Panadero, Javier (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Peidro, David (Universitat Politècnica de València)
Riera Terrén, Daniel (Universitat Oberta de Catalunya. Departament d'Informàtica)

Date:	2023
Abstract:	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.
Grants:	Agencia Estatal de Investigación PDC2022-133957-I00 Agencia Estatal de Investigación PID2022-138860NB-I00 Ministerio de Ciencia e Innovación RED2022-134703-T
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Logistics and transportation ; Metaheuristics ; Simulation ; Fuzzy logic
Published in:	Algorithms, Vol. 16, Issue 12 (December 2023) , art. 570, ISSN 1999-4893

DOI: 10.3390/a16120570

14 p, 524.6 KB

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