A C plus plus application programming interface for co-evolutionary biased random-key genetic algorithms for solution and scenario generation

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Beatriz Brito Oliveira (Author) FEUP; Maria Antónia Carravilla (Author) FEUP; José Fernando Oliveira (Author) FEUP; Maurício G. C. Resende (Author) Other

Journal

Title: Optimization Methods and Software

Vol. 37

Pages: 1065-1086

ISSN: 1055-6788

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00T-HW9

DOI: 10.1080/10556788.2021.1884250

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22