Data of the FFHS mode

With the market demands on quality and efficiency of industrial services increase, the service schemes of the traditional field and factory service modes have gradually been unable to meet user requirements. Therefore, this paper proposes a field-factory hybrid service (FFHS) mode, in which service providers are allowed to transport service resources to the user-specified places for providing field services, and they also can establish temporary factories at certain user sites to provide factory services. On this basis, the FFHS process is analyzed and a bi-objective resource scheduling model considering the emergence of cloud platform is established for it. A two-segment code is designed and an enhanced multi-objective jellyfish search (EMOJS) algorithm is developed for solving the above model. In EMOJS, the elitist preservation strategy, a parameter adaptive adjustment strategy and an opposition-based learning strategy are developed to improve the search performance. Comparison experiments with several state-of-the-art algorithms on some typical bi-objective instances are carried out and prove that EMOJS possesses better search performance