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Adaptive Simulation-Based Optimization for Production Scheduling: A Comparative Study
Open accessAbstract
Production planning and control is an essential activity for all production systems, as its performance directly affects important factors that are fundamental for business competitiveness. The flow shop scheduling problem is one of the most common problems involved in the planning of production systems, being often applied in the real world. The solution to this problem cannot be easily found due to its complexity, which makes it difficult to use methods that return optimal results due to their high computational execution time. Thus, Adaptive Simulation-Based Optimization is a tool with potential application as it considers the stochasticity of the problem, seeking solutions that are aligned with the real scenario through a simulation and optimizing the desired variables. The simulation-based optimization approach consists in a loop between an optimization heuristic/meta-heuristic and a simulation. The optimization inputs the simulation with a parameter set, while the simulation tests all the models generated by the optimization and returns the fitness function values. However, the literature presents several different heuristics, simulation approaches and optimization methodologies to solve the problem. The general objective of the present work is to comparatively evaluate different adaptive simulation-based optimization models for flow shop production systems. Two methods for comparison were considered, which apply a genetic algorithm integrated with a discrete events sim…
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Cited by
Sorted by citations
Performance analysis of production scheduling in Toyota simulation
Mangngenre, S., Indah, A. B., Syamsul, D., Arief, A., & Novawanda, O. (2025) · Acta Logistica · doi:10.22306/al.v12i1.592 · Cited by 1
“…has become an invaluable asset for analyzing and optimizing production systems, allowing companies to assess different scheduling scenarios, pinpoint bottlenecks, and experiment with alternative scheduling strategies in a virtual environment before implementation in real production settings [5-7].”
Metadata
- Authors
- Quadras, D., Frazzon, E. M., Mendes, L. G., Pires, M. C., & Rodriguez, C. M. T.
- Affiliations
- Universidade Federal de Santa Catarina (BR)
- Corresponding author
- Quadras, Djonathan
- Frazzon, Enzo M.
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2022
- Volume
- 55
- Issue
- 10
- Pages
- 424-429
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W4312228380
- Cited by
- 9
- References
- 0
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 2 · 2023: 1
- FWCI
- 0.57
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (FR 3658/1-1)
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (99999.006033/2015-06)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Scheduling and Optimization Algorithms
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Healthcare Operations and Scheduling Optimization
- Keywords
- flow shop scheduling, production scheduling, genetic algorithm, discrete event simulation, dispatching rules, makespan, production planning and control, metaheuristic optimization
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