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Main Authors: Biasoto, Luiza Pellin, de Carvalho, Vinicius Renan, Sichman, Jaime Simão
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.09214
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author Biasoto, Luiza Pellin
de Carvalho, Vinicius Renan
Sichman, Jaime Simão
author_facet Biasoto, Luiza Pellin
de Carvalho, Vinicius Renan
Sichman, Jaime Simão
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2406_09214
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Applying Multi-Agent Negotiation to Solve the Production Routing Problem With Privacy Preserving
Biasoto, Luiza Pellin
de Carvalho, Vinicius Renan
Sichman, Jaime Simão
Artificial Intelligence
Multiagent Systems
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.
title Applying Multi-Agent Negotiation to Solve the Production Routing Problem With Privacy Preserving
topic Artificial Intelligence
Multiagent Systems
url https://arxiv.org/abs/2406.09214