Designing A Multi-Agent System For Improving Supply Chain Performance

Plinere, Darya; Merkurvev, Yuri

doi:10.1109/aieee48629.2019.8976926

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…Los algoritmos genéticos (AG) es una técnica asociada a los problemas de automatización, los cuales buscan mejorar las soluciones a partir de la maximización de funciones objetivo [12]. Los AG pertenecen al área de la computación evolutiva, que se orienta al diseño de algoritmos que aprovechan las teorías de evolución, como lo son la selección natural, la reproducción y la mutación de individuos dentro de una población.…”

Section: Inteligencia Artificialunclassified

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Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Palacio

2021

Rev. politec.

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La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución. Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.

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Section: Inteligencia Artificialunclassified

“…En [58] proponen un sistema de percepción y razonamiento sobre una cadena de suministro que puede ser atendida por un agente y su percepción; así mismo, En [12] proponen una aproximación basada en agentes para la distribución y razonamiento de funciones.…”

Section: Agentes Inteligentesunclassified

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Palacio

2021

Rev. politec.

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“…It is proposed to develop four agents [6] that cover all the supply chain management functions of the manufacturer:…”

Section: Agent Algorithmsmentioning

confidence: 99%

“…From a material management point of view [6], stocks are defined as "a usable but idle resource with a certain economic value". Physical stocks must be available to meet demand, otherwise it will lead to production delays, shortages and / or customer dissatisfaction.…”

Section: Inventory Management Agent Developmentmentioning

confidence: 99%

Multi-Agent System Development and Application for Supply Chain Management Tasks

Plinere

Aļeksejeva

Merkuryev

2021

ITMS

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In today’s dynamically changing environment, we need to be able to respond in a timely manner to changes in supply chain processes. Software agents are successfully used in supply chain management tasks for a variety of purposes. The behaviour of agents is determined by the purpose of their development, and the effectiveness of the use of agents is considered in accordance with the purpose of their development. The paper presents research on the development of a multi-agent system for supply chain management, focusing on the steps of developing a multi-agent system. The choice of each algorithm for agents is analysed and argued. The application of the developed multi-agent system for supply chain management is also described in the paper. The efficiency of application of the developed multi-agent system is presented as well.

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Flexibility measurement model of multi-agent systems

Benaboud¹,

Marir²

2020

MGS

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Flexibility is considered as one of the key objectives of agent-based technology. Despite this, we still lack a fundamental understanding of just what “flexibility in multi-agent system (MAS)” really is. Two main questions must be asked. First, how do agents and MAS achieve a high degree of flexibility? Second, what makes one agent or one MAS more flexible than others agents or others MASs? This paper addresses the answer to these two questions by proposing an ontology of the flexibility property and a mathematical measurement model for this property. The proposed ontology gives a comprehensive view of the flexibility by decomposing it on several characteristics and presents several techniques for implementing each characteristic. In addition, it relates these characteristics to MAS components. The proposed model presents a set of metrics for measuring the different characteristics of the flexibility property. The proposed metrics have been applied to JADE applications using a tool developed for this purpose.

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Designing A Multi-Agent System For Improving Supply Chain Performance

Cited by 3 publications

References 8 publications

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Multi-Agent System Development and Application for Supply Chain Management Tasks

Flexibility measurement model of multi-agent systems

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