Hybrid Honey Bees Mating Optimization Algorithm for Identifying the Near-Optimal Solution in Web Service Composition

In: Computing and Informatics, vol. 36, no. 5

V.r. Chifu - C.b. Pop - I. Salomie - E.s. Chifu

Detaily:

Rok, strany: 2017, 1143 - 1172

Kľúčové slová:

Honey Bees Mating Optimization, genetic algorithms, tabu search, reinforcement learning, web service composition

DOI: https://doi.org/10.4149/cai_2017_5_1143

O článku:

This paper addresses the problem of optimality in semantic Web service composition by proposing a hybrid nature-inspired method for selecting the optimal or near-optimal solution in semantic Web Service Composition. The method hybridizes the Honey-Bees Mating Optimization algorithm with components inspired from genetic algorithms, reinforcement learning, and tabu search. To prove the necessity of hybridization, we have analyzed comparatively the experimental results provided by our hybrid selection algorithm versus the ones obtained with the classical Honey Bees Mating Optimization algorithm and with the genetic-inspired algorithm of Canfora et al.

Ako citovať:

ISO 690:

Chifu, V., Pop, C., Salomie, I., Chifu, E. 2017. Hybrid Honey Bees Mating Optimization Algorithm for Identifying the Near-Optimal Solution in Web Service Composition. In Computing and Informatics, vol. 36, no.5, pp. 1143-1172. 1335-9150. DOI: https://doi.org/10.4149/cai_2017_5_1143

APA:

Chifu, V., Pop, C., Salomie, I., Chifu, E. (2017). Hybrid Honey Bees Mating Optimization Algorithm for Identifying the Near-Optimal Solution in Web Service Composition. Computing and Informatics, 36(5), 1143-1172. 1335-9150. DOI: https://doi.org/10.4149/cai_2017_5_1143

O vydaní: