Optimizing Transport Logistics under Uncertainty with Simheuristics: Concepts, Review and Trends

Juliana Castaneda, Elnaz Ghorbani, Majsa Ammouriova, Javier Panadero and Angel A. Juan
Additional contact information
Juliana Castaneda: Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Elnaz Ghorbani: Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Majsa Ammouriova: Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Javier Panadero: Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Angel A. Juan: Department of Applied Statistics and Operations Research, Universitat Politècnica de València, 03801 Alcoy, Spain

Logistics, 2022, vol. 6, issue 3, 1-15

Abstract: Background: Uncertainty conditions have been increasingly considered in optimization problems arising in real-life transportation and logistics activities. Generally, the analysis of complex systems in these non-deterministic environments is approached with simulation techniques. However, simulation is not an optimization tool. Hence, it must be combined with optimization methods when our goal is to: (i) minimize operating costs while guaranteeing a given quality of service; or (ii) maximize system performance using limited resources. When solving NP-hard optimization problems, the use of metaheuristics allows us to deal with large-scale instances in reasonable computation times. By adding a simulation layer to the metaheuristics, the methodology becomes a simheuristic, which allows the optimization element to solve scenarios under uncertainty. Methods: This paper reviews the indexed documents in Elsevier Scopus database of both initial as well as recent applications of simheuristics in the logistics and transportation field. The paper also discusses open research lines in this knowledge area. Results: The simheuristics approaches to solving NP-hard and large-scale combinatorial optimization problems under uncertainty scenarios are discussed, as they frequently appear in real-life applications in logistics and transportation activities. Conclusions: The way in which the different simheuristic components interact puts a special emphasis in the different stages that can contribute to make the approach more efficient from a computational perspective. There are several lines of research that are still open in the field of simheuristics.

Keywords: simheuristics; transportation; logistics; optimization; uncertainty (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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