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

Authors

  • Viorica Rozina Chifu Tehnical University of Cluj-Napoca, Department of Computer Science, Cluj-Napoca
  • Cristina Bianca Pop Tehnical University of Cluj-Napoca, Department of Computer Science, Cluj-Napoca
  • Ioan Salomie Tehnical University of Cluj-Napoca, Department of Computer Science, Cluj-Napoca
  • Emil Stefan Chifu Tehnical University of Cluj-Napoca, Department of Computer Science, Cluj-Napoca

Abstract

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.

Downloads

Download data is not yet available.

Downloads

Published

2017-12-19

How to Cite

Chifu, V. R., Pop, C. B., Salomie, I., & Chifu, E. S. (2017). Hybrid Honey Bees Mating Optimization Algorithm for Identifying the Near-Optimal Solution in Web Service Composition. COMPUTING AND INFORMATICS, 36(5), 1143–1172. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/2017_5_1143

Most read articles by the same author(s)