Artificial Bee Colony with Cuckoo Search for Solving Service Composition

In recent years, cloud computing has provided a Software As A Service (SaaS) platform where the software can be reused and applied to fulfill complicated user demands according specific Quality of Services (QoS) constraints. The requirements are formulated as workflow consisting set tasks. However, many services may satisfy functionality each task; thus, searching for composition optimal service while maximizing QoS is an NP-hard problem. This work will introduce hybrid Artificial Bee Colony (ABC) with Cuckoo Search (CS) algorithm untangle ABC well-known metaheuristic that when dealing different problems outstanding record performance. suffers from slow convergence Therefore, CS used overcome ABC’s limitations by allowing abandoned bees enhance their search override local optimum. proposed been tested on 19 datasets then compared two standard algorithms (ABC CS) three state-of-the-art swarm-based algorithms. addition, extensive parameter study experiments were conducted up algorithm’s parameters. results indicate outperforms in comparison criteria (best fitness value, average execution time) overall 30 runs. Furthermore, also exhibits better performance than state–of–the–art over