Abstract
The paper presents a hybridization of two ideas closely related to metaheuristic computing, namely Portfolio Optimization (researched by Xin Yao et al.) and Translation of Representation for different metaheuristics (researched by Byrski et al.). Thus, difficult problems (discrete optimization) are approached by a sequential run through a number of steps of different metaheuristics, providing the translation of representation (since the algorithms are completely different). Therefore, close cooperation of e.g. ACO, PSO, and GA is possible. The results refer to unaltered algorithms and show the superiority of the constructed hybrid.
| Original language | English |
|---|---|
| Pages (from-to) | 57-75 |
| Number of pages | 19 |
| Journal | Journal of Artificial Intelligence and Soft Computing Research |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2025 |
| Externally published | Yes |
Free Keywords
- metaheuristics
- portfolio optimization
- transport problems
ASJC Scopus subject areas
- Information Systems
- Modelling and Simulation
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Artificial Intelligence
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