An Improved Whale Optimization Algorithm for Web Service Composition

In the current circumstance, Web Service Composition (WSC) was introduced to address complex user needs concerning Quality of Services (QoS). WSC problem, are divided into a set tasks. The corresponding web services retrieved from discovery according functionality each task, and have different non-functional constraints, such as QoS. problem is multi-objective optimization classified an NP-hard problem. whale algorithm (WOA) proven solve problems, it has advantage easy implementation with few control parameters. this work, we contribute improving WOA algorithm, where strategies enhance its performance shortcomings, namely slow convergence speed, which produces low solution accuracy for proposed named Improved Whale Optimization Algorithm (IWOA) three WOA. Firstly, Sine chaos theory initiate WOA’s population initialization diversity. Secondly, Lévy flight mechanism exploitation exploration by maintaining whales’ Further, neighborhood search trade-off between searching mechanisms. Different experiments conducted datasets on 12 scales (small, medium, large), compared standard five state-of-the-art swarm-based algorithms 30 independent runs. Furthermore, four evaluation criteria used validate comparison: average fitness value, best values, deviation, execution time. results show that IWOA enhanced algorithm’s performance, got better values variation all datasets. However, ranked second regarding time after WOA, sometimes third OABC, reasonable because strategies.