Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Similars in SciELO
Share
Enfoque UTE
On-line version ISSN 1390-6542Print version ISSN 1390-9363
Abstract
ARBOLEDA-CASTRO, Lorena; CEDENO-FUENTES, Olga; JACHO-SANCHEZ, Iván and NOVOA-HERNANDEZ, Pavel. An evolutionary computational approach for the dynamic Stackelberg competition problems. Enfoque UTE [online]. 2016, vol.7, n.2, pp.10-24. ISSN 1390-6542. https://doi.org/10.29019/enfoqueute.v7n2.92.
Stackelberg competition models are an important family of economical decision problems from game theory, in which the main goal is to find optimal strategies between two competitors taking into account their hierarchy relationship. Although these models have been widely studied in the past, it is important to note that very few works deal with uncertainty scenarios, especially those that vary over time. In this regard, the present research studies this topic and proposes a computational method for solving efficiently dynamic Stackelberg competition models. The computational experiments suggest that the proposed approach is effective for problems of this nature.
Keywords : Stackelberg competition; evolutionary dynamic optimization; bilevel optimization; metaheuristics..