Simheuristics applications: dealing with uncertainty in logistics, transportation, and other supply chain areas
Simheuristics applications: dealing with uncertainty in logistics, transportation, and other supply chain areas
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.
3048-3059
Juan, Angel A.
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David Kelton, W.
ef77c147-da21-40f6-bf63-85d1b67e142b
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Faulin, Javier
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4 February 2019
Juan, Angel A.
a08d6aac-1e9b-4537-81a7-29a1ba791f26
David Kelton, W.
ef77c147-da21-40f6-bf63-85d1b67e142b
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Faulin, Javier
b50f3d35-0d75-4c02-be1c-57bb671fa5ae
Juan, Angel A., David Kelton, W., Currie, Christine S.M. and Faulin, Javier
(2019)
Simheuristics applications: dealing with uncertainty in logistics, transportation, and other supply chain areas.
In 2018 Winter Simulation Conference (WSC).
vol. 2018-December,
IEEE.
.
(doi:10.1109/WSC.2018.8632464).
Record type:
Conference or Workshop Item
(Paper)
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.
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WSC18 Kelton Simheuristics
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Accepted/In Press date: 20 August 2018
e-pub ahead of print date: December 2018
Published date: 4 February 2019
Venue - Dates:
WSC 2018 Winter Simulation Conference: Simulation for a Noble Cause, , Gothenburg, Sweden, 2018-12-09 - 2018-12-12
Identifiers
Local EPrints ID: 429148
URI: http://eprints.soton.ac.uk/id/eprint/429148
ISSN: 1558-4305
PURE UUID: 5445f42f-b33b-4667-8ba0-44f7e0af0058
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Date deposited: 22 Mar 2019 17:30
Last modified: 16 Mar 2024 03:30
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Contributors
Author:
Angel A. Juan
Author:
W. David Kelton
Author:
Javier Faulin
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