Real-time auction logistics with IoT-based cloud platform

Abstract

Major auction trading service providers have solved technological problems of dealing with millions of simultaneous biddings. Unfortunately, it is challenging to provide logistics that fulfils massive and lumpy demands in auction industry. Dynamic uncertainties make the auction planning, scheduling and execution control more complex. Moreover, the existing centralized approaches are frequently limited in their efficiency due to the large variations of deployed assets and numerous auction parameters to be considered. Meanwhile, Internet of Things (IoT) and cloud technology have been widely used in several industrial applications. These emerging technologies can enable real-time data collection, proactive response actions, as well as improved process visibility. Based on intelligent platform technologies, this thesis is among the first to systematically propose the concept of real-time auction logistics (AL). It is an essential part of perishable supply chain trading that plans, implements and controls the efficient, effective flow and storage of products, services and related information driven by auctions to meet both operators and customers' requirements. A research framework is established to provide guidelines for investigating real-time planning, scheduling and execution control in auction logistics. Four typical scenarios are examined. The first scenario presents cloud-based auction logistics information platform following three-layer standardized architecture while considering auction characteristics. Motivated by an industrial case of flower auction trading, practitioners are confronted with challenges to fully utilize real-time decision-makings to synchronize both material flow and information flow for multiple users. The proposed cloud platform is expected to make auction planning scalable with respect to transient demands by implementing autonomous logistics. Through the integration of IoT and cloud computing technologies, interactive omnichannel auction bidding is established. Heterogeneous physical assets such as auction trolleys could be easily virtualized, traced and tracked, and managed in the cloud. The second scenario demonstrates an adaptive scheduling for perishable goods auction. Following the hybrid flowshop scheduling (HFS) classification, a timely model for trolley loading and auction trading stages is developed. It is an extension of a typical HFS problem with several characteristics. A heuristic-based solution approach is proposed to minimize either makespan or value loss using a set of dispatching rules. The simulation experiments justify that schedulers can flexibly select dispatching rules under various demand patterns and operation time windows, as well as system configurations and trolley sizes. The third scenario discusses a new paradigm of goods-to-person auction execution method using cloud auction robot (CAR). CARs are used to pick up and deliver the auction products according to the given commands in real-time. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behaviour of CAR-Agents in handling the real-time events and associated data. The CARES is flexible to cope with different auction mechanisms and processes with high re-configurability. A system prototype is also validated through physical emulations. Experiment results show that the CARES could well schedule the tasks for each robot to minimize its waiting time. The total execution time is reduced by 33% on average. Space utilization for each auction studio is improved by 50% approximately. The fourth scenario verifies and validates the proposed platform technologies with real-time methods (i.e., auction planning, scheduling and execution control) via a case study. The near-life pilot implementation examines how the system is able to facilitate the auction activities and decision-making procedures. Lessons and insights from quantitative and qualitative aspects are also discussed. In this research, real-time planning, scheduling and execution control in auction logistics are investigated. The related operation mechanisms and platform technologies are developed accordingly. This comprehensive study of auction logistics is of great value not only to researchers who desire to extend their research into this new area, but also to practitioners who are interested in examining the impacts of logistics factors on operation performance of perishable goods auction.