Motivated by the business model called“community group buying”(CGB),which has emerged in China and some countries in Southeast Asia,such as Singapore and Indonesia,we develop algorithms that could help CGB platforms...
详细信息
Motivated by the business model called“community group buying”(CGB),which has emerged in China and some countries in Southeast Asia,such as Singapore and Indonesia,we develop algorithms that could help CGB platforms match consumers with stage-stations(the picking up center under the CGB mode).By altering the fundamental design of the existing hierarchy algorithms,improvements are *** is proven that our method has a faster running speed and greater space *** algorithms avoid traversal and compress the time complexities of matching a consumer with a stage-station and updating the storage information to O(logM)and O(MlogG),where M is the number of stage-stations and G is that of the platform’s stock-keeping *** comparisons of our algorithms with the current methods of CGB platforms show that our approaches can effectively reduce delivery *** interesting observation of the simula-tions is worthy of note:Increasing G may incur higher costs since it makes inventories more dispersed and delivery prob-lems more complicated.
With the development of SOA based on web services, there are more and more web services with same interface and similar function. How to find and choose the best web service is an important problem that all SOA enterp...
详细信息
ISBN:
(纸本)9780769547923
With the development of SOA based on web services, there are more and more web services with same interface and similar function. How to find and choose the best web service is an important problem that all SOA enterprises face. QoS is used to describe the quality criteria of a web service. In this paper, a new algorithm of web service hierarchy base on QoS similarity has been proposed, which is concerned with meeting requirements of service consumers and the satisfaction with load requirement.
Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sa...
详细信息
Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor- intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and sim- ilarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface （GUI） tool named BioCluster. This tool was designed for automated clustering and iden- tification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering （HC） and the Improved Hierarchical Clustering （IHC）, a modified algorithm that was developed specifically for the clustering and identification of within this species. IHC takes into account the variability in result of 1-47 biochemical tests family. This tool also provides different options to optimize the clus- tering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http：//***/ biocluster/.
暂无评论