The goal of QoS aware web service composition (QoS-WSC) is to provide new functionalities and find a best combination of services to meet complex needs of users. QoS of the resulting composite service should be optimized. QoS-WSC is a global multi-objective optimization problem belonging to NP-hard class given the number of available services. Most of existing approaches reduce this problem to a single-objective problem by aggregating different objectives, which leads to a loss of information. An alternative issue is to use Pareto-based approaches. The Pareto-optimal set contains solutions that ensure the best trade-off between conflicting objectives. In this paper, a new multi-objective meta-heuristic bio-inspired Pareto-based approach is presented to address the QoS-WSC, it is based on Elephants Herding Optimization (EHO) algorithm. EHO is characterised by a strategy of dividing and combining the population to sub population (clan) which allows exchange of information between local searches to get a global optimum. However, the application of others evolutionary algorithms to this problem cannot avoids the early stagnancy in a local optimum. In this paper a discrete and multi-objective version of EHO will be presented based on a crossover operator. Compared with SPEA2 (Strength Pareto Evolutionary Algorithm 2) and MOPSO (Multi-Objective Particle Swarm Optimization algorithm), the results of experimental evaluation show that our improvements significantly outperform the existing algorithms in term of Hypervolume, Set Coverage and Spacing metrics.
Accepté le :
DOI : 10.1051/ro/2017049
Mots-clés : QoS, Multi-Objective optimization, Pareto Set, Bio-inspired Algorithms, Elephants Herding optimization, Web service composition
@article{RO_2019__53_2_445_0,
author = {Chibani Sadouki, Samia and Tari, Abdelkamel},
title = {Multi-objective and discrete {Elephants} {Herding} {Optimization} algorithm for {QoS} aware web service composition},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {445--459},
publisher = {EDP-Sciences},
volume = {53},
number = {2},
year = {2019},
doi = {10.1051/ro/2017049},
zbl = {1436.68388},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2017049/}
}
TY - JOUR AU - Chibani Sadouki, Samia AU - Tari, Abdelkamel TI - Multi-objective and discrete Elephants Herding Optimization algorithm for QoS aware web service composition JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2019 SP - 445 EP - 459 VL - 53 IS - 2 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2017049/ DO - 10.1051/ro/2017049 LA - en ID - RO_2019__53_2_445_0 ER -
%0 Journal Article %A Chibani Sadouki, Samia %A Tari, Abdelkamel %T Multi-objective and discrete Elephants Herding Optimization algorithm for QoS aware web service composition %J RAIRO - Operations Research - Recherche Opérationnelle %D 2019 %P 445-459 %V 53 %N 2 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2017049/ %R 10.1051/ro/2017049 %G en %F RO_2019__53_2_445_0
Chibani Sadouki, Samia; Tari, Abdelkamel. Multi-objective and discrete Elephants Herding Optimization algorithm for QoS aware web service composition. RAIRO - Operations Research - Recherche Opérationnelle, Tome 53 (2019) no. 2, pp. 445-459. doi : 10.1051/ro/2017049. http://www.numdam.org/articles/10.1051/ro/2017049/
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