A Hybrid Artificial Bee Colony Algorithm to Solve Multi-objective Hybrid Flowshop in Cloud Computing Systems

This paper proposes a local search enhanced hybrid artificial bee colony algorithm (LABC) for solving the multi-objective flexible task scheduling problem in Cloud computing system. The task scheduling is modeled as a hybrid flow shop scheduling (HFS) problem. In multiple objectives HFS problems, three objectives, i.e., minimum of the makespan, maximum workload, and total workload are considered simultaneously. In the proposed algorithm, each solution is represented as an integer string. A deep-exploitation function is developed, which is used by the onlooker bee and the best food source found so far to complete a deep level of search. The proposed algorithm is tested on sets of the well-known benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed LABC algorithm is shown against several efficient algorithms from the literature.