e98c35c4721efe0362a46e1a0c1b0784 Alg_a2023v16n12p570.pdf 7d492a48bed742b8bb15013bebdb58039d1352e7 Alg_a2023v16n12p570.pdf e65eb20fb8ea1e5fe9ee1deedbc41531422b92c8ee919e424ade43605936dd13 Alg_a2023v16n12p570.pdf Title: Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics Subject: 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. Keywords: logistics and transportation; metaheuristics; simulation; fuzzy logic Author: Angel A. Juan, Markus Rabe, Majsa Ammouriova, Javier Panadero, David Peidro and Daniel Riera Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Sat Dec 16 07:20:53 2023 CET ModDate: Sat Dec 16 07:23:46 2023 CET Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 14 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 537193 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- XDZUVF+URWPalladioL-Bold Type 1 Custom yes yes yes 10 0 OHFTZM+URWPalladioL-Roma Type 1 Custom yes yes yes 16 0 VEGJPA+URWPalladioL-Ital Type 1 Custom yes yes yes 21 0 WCYBKT+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 41 0 XQZHNR+PazoMath-Italic Type 1 Builtin yes yes yes 69 0 CZKGAS+CMR10 Type 1 Builtin yes yes yes 74 0 UZKIAN+CMEX10 Type 1 Builtin yes yes yes 84 0 QIELJB+CMMI10 Type 1 Builtin yes yes yes 89 0 KHUFRV+CMSY10 Type 1 Builtin yes yes yes 94 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2024-05-11 02:46:17 CEST RepresentationInformation: Alg_a2023v16n12p570.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2024-05-10 16:11:05 CEST Size: 537193 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 282 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Modeling Uncertainty in Logistics and Transportation Destination: section.2 Item: Title: Modeling Optimization Problems with General Uncertainty Destination: section.3 Item: Title: A Review of the Simheuristics Concept and Recent Applications Destination: section.4 Item: Title: Extending Simheuristics with Fuzzy Logic Destination: section.5 Item: Title: Recent Applications of Fuzzy Simheuristics Destination: section.6 Item: Title: Trends and Open Research Lines Destination: section.7 Item: Title: Conclusions Destination: section.8 Item: Title: References Destination: section.9 Info: Title: Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics Author: Angel A. Juan, Markus Rabe, Majsa Ammouriova, Javier Panadero, David Peidro and Daniel Riera Subject: 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. 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