2026-06-29T22:16:57Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/74412024-05-10T10:37:31Zcom_10259_5645com_10259_5086com_10259_2604col_10259_5646
Repositorio Institucional de la Universidad de Burgos
author
Costas-Gual, José
author
Puche Regaliza, Julio César
author
Ponte, Borja
author
Gupta, Mahesh C.
2023-02-13T11:41:36Z
2023-02-13T11:41:36Z
2023-02
1569-190X
http://hdl.handle.net/10259/7441
10.1016/j.simpat.2022.102660
Product-mix problems, where a range of products that generate different incomes compete for a
limited set of production resources, are key to the success of many organisations. In their
deterministic forms, these are simple optimisation problems; however, the consideration of stochasticity may turn them into analytically and/or computationally intractable problems. Thus,
simulation becomes a powerful approach for providing efficient solutions to real-world productmix problems. In this paper, we develop a simulator for exploring the cost of uncertainty in these
production systems using Petri nets and agent-based techniques. Specifically, we implement a
stochastic version of Goldratt’s PQ problem that incorporates uncertainty in the volume and mix
of customer demand. Through statistics, we derive regression models that link the net profit to the
level of variability in the volume and mix. While the net profit decreases as uncertainty grows, we
find that the system is able to effectively accommodate a certain level of variability when using a
Drum-Buffer-Rope mechanism. In this regard, we reveal that the system is more robust to mix
than to volume uncertainty. Later, we analyse the cost-benefit trade-off of uncertainty reduction,
which has important implications for professionals. This analysis may help them optimise the
profitability of investments. In this regard, we observe that mitigating volume uncertainty should
be given higher consideration when the costs of reducing variability are low, while the efforts are
best concentrated on alleviating mix uncertainty under high costs.
eng
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Agent-based modelling
Model-driven decision support system
Petri nets
Product-mix problem
Simulation
Theory of constraints
An agent-based simulator for quantifying the cost of uncertainty in production systems
info:eu-repo/semantics/article
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