Automated Negotiation for Future Supply Chains
patterns. The framing is intentionally aligned with the agent economy, the Gartner machine-customer thesis, and a five-year projection of how supply-chain contracting will evolve. Readers who want the algorithmic detail behind the numbers reported in Section 5 are referred to Ando et al. [ 3 ] for the delivery-date-adjustment system architecture and to Mohammad & Chen [ 7 ] for the multimodal-forecasting-driven utility specification used in the use-cases of Section 6. Readers interested in the standardization and ecosystem work referenced throughout are pointed to the Autonomous Negotiation SCM Consortium [ 16 ] which NEC convened in Japan to advance this agenda across industry and academia.
Figure
Introduction: The Agent Economy Meets the Supply Chain-1: From single-agent AI through single-owner multi-agent systems to cross-boundary MAS, where automated negotiation provides a coordination mechanism between agents from different organizations.
3 THREE CORE CLAIMS
• Coordination across organizational boundaries is a distinct problem from coordination inside a single organization, because each side ' s preferences( utility function) and policies are typically private. Automated negotiation provides one principled mechanism for closing that coordination gap while preserving privacy of preferences.
• Initial production evidence is encouraging but limited in scope. NEC ' s 2024 deployment at an NEC group company closed 95 % of delivery-date adjustments( 133 of 140) with a median time of 77 seconds across 1,300 product types and 10 suppliers, compressed from a manual baseline of three hours to two days [ 3, 10 ]; the NEC – XMPro DTC testbed reaches win – win delivery-schedule agreements in roughly two minutes on a search space of over half a million candidate schedules [ 9 ]. These results are consistent across several independent settings but each remains a relatively narrow operational slice.
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