The Bundling of Multiple Requirements for Maximizing the Utilization of Service Resources

We present a service resource selection and scheduling approach capable of maximizing the resource utilization rate (RUT) and the requirement satisfaction degree (RSD) by bundling multiple customer requirements (CRs). In traditional approaches, each CR is optimally satisfied by independently selecting a set of candidate service resources. This possibly leads to a low RUT and low RSD. In our approach, multiple CRs raised within a certain time period are bundled and a virtual service resource (VSR) is constructed to satisfy these requirements simultaneously by making full use of the sharing nature of resources. Specifically, each CR is first decomposed into a set of atomic requirements, which are then re-aggregated according to their requested resources. For four types of service-resource sharing patterns, we present the corresponding greedy algorithms that construct the VSR and its scheduling. The goals of our methods are (1) maximizing the satisfaction degree of CRs and (2) maximizing the RUT of service resources. The effectiveness of our approach is demonstrated in an experiment for a typical scenario of ocean transportation service.