Variable Neighborhood Search and Tabu Search for the Web Service Selection Problem

Abstract

When a composition of web services is needed to achieve some desired functionality it is necessary to choose a particular service for each of the components. There may be a large number of web services offering similar functionality and when choosing a service, the decision should be based on the relevant Quality of Service (QoS) attributes. Therefore, the main goal of the web service selection problem is to choose the composition with the best performance which also satisfies certain constraints regarding the required QoS levels. Since for large problems the exact solution may be impossible to reach in an acceptable timeframe, due to the exponentially growing number of possible combinations, for the first time Variable Neighborhood Search (VNS) is introduced for solving this problem. The greedy-add algorithm with back-tracking is introduced for obtaining the initial solution and a better solution is sought through VNS as well as Tabu Search. The experimental results demonstrate the efficiency of the proposed approaches.