Applying Multi-Agent Negotiation to Solve the Production Routing Problem With Privacy Preserving

TL;DR

This paper introduces a multi-agent negotiation framework within a hybrid system to solve complex supply chain routing problems while preserving privacy, demonstrating effectiveness through real-world applications.

Contribution

It presents a novel integration of multi-agent negotiation with optimization algorithms for privacy-preserving supply chain routing.

Findings

Effective in real-world supply chain scenarios

Enhances privacy preservation in routing decisions

Improves coordination among supply chain entities

Abstract

This paper presents a novel approach to address the Production Routing Problem with Privacy Preserving (PRPPP) in supply chain optimization. The integrated optimization of production, inventory, distribution, and routing decisions in real-world industry applications poses several challenges, including increased complexity, discrepancies between planning and execution, and constraints on information sharing. To mitigate these challenges, this paper proposes the use of intelligent agent negotiation within a hybrid Multi-Agent System (MAS) integrated with optimization algorithms. The MAS facilitates communication and coordination among entities, encapsulates private information, and enables negotiation. This, along with optimization algorithms, makes it a compelling framework for establishing optimal solutions. The approach is supported by real-world applications and synergies between MAS and optimization methods, demonstrating its effectiveness in addressing complex supply chain optimization problems.