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A C++ application programming interface for co-evolutionary biased random-key genetic algorithms for solution and scenario generation.
- Source :
-
Optimization Methods & Software . Jun2022, Vol. 37 Issue 3, p1065-1086. 22p. - Publication Year :
- 2022
-
Abstract
- This paper presents a C++ application programming interface for a co-evolutionary algorithm for solution and scenario generation in stochastic problems. Based on a two-space biased random-key genetic algorithm, it involves two types of populations that are mutually impacted by the fitness calculations. In the solution population, high-quality solutions evolve, representing first-stage decisions evaluated by their performance in the face of the scenario population. The scenario population ultimately generates a diverse set of scenarios regarding their impact on the solutions. This application allows the straightforward implementation of this algorithm, where the user needs only to define the problem-dependent decoding procedure and may adjust the risk profile of the decision-maker. This paper presents the co-evolutionary algorithm and structures the interface. We also present some experiments that validate the impact of relevant features of the application. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10556788
- Volume :
- 37
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Optimization Methods & Software
- Publication Type :
- Academic Journal
- Accession number :
- 159583377
- Full Text :
- https://doi.org/10.1080/10556788.2021.1884250