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Population diversity in ant-inspired optimization algorithms

Byrski Aleksander, Węgrzyński Krzysztof, Radwański Wojciech, Starzec Grażyna, Starzec Mateusz, Bargiel Monika, Urbańczyk Aleksandra, Kisiel-Dorohinicki Marek

Computer Science

2021

T. 22 (3)

297–320

Measuring the diversity in evolutionary algorithms that work in real-value search spaces is often computationally complex, but it is feasible; however, measuring the diversity in combinatorial domains is practically impossible. Nevertheless, in this paper we propose several practical and feasible diversitymeasurement techniques that are dedicated to ant colony optimization algorithms, leveraging the fact that we can focus on a pheromone table even though an analysis of the search space is at least an NP problem where the direct outcomes of the search are expressed and can be analyzed. Besides sketching out the algorithms, we apply them to several benchmark problems and discuss their efficacy.

Desynchronization of simulation and optimization algorithms in HPC environment

Starzec Mateusz, Starzec Grażyna, Paciorek Mateusz

Computer Science

2020

T. 21 (3)

319–333

The need for the scalability of an algorithm is essential when one wants to utilize an HPC infrastructure in an efficient and reasonable way. In such infrastructures, synchronization affects the efficiency of the parallel algorithms. However, one can consider introducing certain means of desynchronization in order to increase the scalability. Allowing certain messages to be omitted or delayed can be easily accepted in the case of metaheuristics. Furthermore, some simulations can also follow this pattern and thereby handle bigger environments. The paper presents a short survey on the desynchronization idea, pointing out already obtained results, or sketching out future work focused on scaling the parallel and distributed computing or simulation algorithms.