Introduction

Today’s global internet economy is increasingly putting a premium on the ability of enterprises to quickly adapt to changing market conditions as well as other disruptive events. This demand for increased agility applies to both internal operations as well as relationships with external business partners. The e-Supply Chain Management Laboratory conducts interdisciplinary research on decision support tools and advanced technologies aimed at significantly increasing enterprise supply chain agility. Our work combines the use and development of heuristic search techniques, machine learning, planning and scheduling, computational game theory, mixed initiative problem solving, and artificial intelligence techniques. Over the years, the Laboratory has developed a number of supply chain technologies and tools in collaboration with industry and government organizations (e.g. Raytheon, Mitsubishi, IBM, the US Army, SAP, NSF, DARPA) with many of these techniques eventually leading to successful deployment and/or commercialization efforts.

Current Research Focus:

  • Adaptive Supply Chain Trading and Negotiation: We are developing and evaluating automated and semi-automated negotiation techniques aimed at empowering enterprises to more effectively evaluate large numbers of trading options. This includes exploring different market mechanisms (e.g. different negotiation protocols, different contractual arrangements) in different supply chain environments (e.g. different levels of competition and uncertainty).
  • Integrated Sourcing, Procurement, Planning and Bidding: The focus here is on highly responsive decision support architectures that closely coordinate sourcing, procurement, planning and bidding activities – in contrast to traditional ERP architectures where these decisions are generally decoupled
  • Real-time Ordering Promising: Available-To-Promise (ATP), Capable-To-Promise (CTP) and Profitable-To-Promise (PTP) functionality.
    Mixed initiative decision support environments intended to leverage our automated planning, scheduling and trading technologies while allowing users to remain in control of key decisions
  • Workflow Management Technologies: We have developed a meta-control architecture that enables users to effectively keep track of complex tasks involving interactions with a large number of other roles across multiple organizations.
  • Web Service Technologies for Secure Supply Chain Collaboration: This includes the development of semantic web service architectures and decentralized trust management technologies for virtual enterprise collaboration.

Some of this research is conducted in collaboration with the University of Michigan under a joint 5-year NSF/ITR grant – MASCHINE project, and also involves a collaboration with the EU TrustCoM project.