Fuzzified Hybrid Metaheuristics for QoS-Aware Service Composition

Service composition has been a centric challenge in various distributed computational paradigms arising from the necessity of composing services to deliver more complicated computing tasks. In many cases, service composition was the process of selecting the optimal set of services from a repository of available services, which led to a multi-objective combinatorial optimization problem falling in the category of NP-hard. As a result, seeking optimal solutions in a minimum time budget has been a continuous quest in the research agenda. Metaheuristics and hybrid metaheuristics have been the primary avenues to address this problem. Nonetheless, metaheuristics suffer from randomicity, slow or premature convergence and stochastic behaviour. A plethora of hybridization methods leveraging operator modification is evident in existing literature. This paper proposes a fuzzy hybrid metaheuristics using fuzzy linguistics search operator to accelerate convergence and minimize the stochastic behaviours of metaheuristics to achieve a stable search mechanism.