Abstract
Optimization problems arising in real-life transportation and logistics need to consider uncertainty conditions (e.g., stochastic travel times, etc.). Simulation is employed in the analysis of complex systems under such non-deterministic environments. However, simulation is not an optimization tool, so it needs to be combined with optimization methods whenever the goal is to: (i) maximize the system performance using limited resources; or (ii) minimize its operations cost while guaranteeing a given quality of service. When the underlying optimization problem is NP-hard, metaheuristics are required to solve large-scale instances in reasonable computing times. Simheuristics extend metaheuristics by adding a simulation layer that allows the optimization component to deal with scenarios under uncertainty. This paper reviews both initial as well as recent applications of simheuristics, mainly in the area of logistics and transportation. The paper also discusses current trends and open research lines in this field.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
