Route planning model of multi-agent system for a supply chain management

Zolfpour-Arokhlo, Mortaza; Selamat, Ali; Hashim, Siti Zaiton Mohd

doi:10.1016/j.eswa.2012.08.040

Cited by 19 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, the resulting complexity of the algorithm in [35] is exponential with the number of leaves of the tree. Further, in [47] a multi-agent route planner performs a local optimization by each agent with respect to different criteria: traffic load, road safety, road type, and weather condition. After the local optimization, a global graph is built and an agent determines the travelling time.…”

Section: B Related Work and Paper Positioningmentioning

confidence: 99%

“…After the local optimization, a global graph is built and an agent determines the travelling time. Differently from [35] and [47], in our multi-agent ATIS each agent determines a piece of the global solution, so that with the agents' coalition, an overall solution may be found with a reduced complexity with respect to the centralized case. Moreover, Adler et al [2] propose a multi-agent approach for cooperative traffic management that employs negotiation to solve the pre-trip route assignment in a multi-objective framework, but the system does not take into account sustainability that is essential in a co-modal framework.…”

Section: B Related Work and Paper Positioningmentioning

confidence: 99%

See 1 more Smart Citation

A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework

Dotoli

Zgaya

Russo³

et al. 2017

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

We present an advanced traveler information system (ATIS) for public and private transportation, including vehicle sharing and pooling services. The ATIS uses an agentbased architecture and multi-objective optimization to answer trip planning requests from multiple users in a co-modal setting, considering vehicle preferences and conflicting criteria. At each set of users' requests, the transportation network is represented by a co-modal graph that allows decomposing the trip planning problem into smaller tasks: the shortest routes between the network nodes are determined and then combined to obtain possible itineraries. Using multi-objective optimization, the set of uservehicle-route combinations according to the users' preferences is determined, ranking all possible route agents' coalitions. The ATIS is tested for the real case study of the Lille metropolitan area (Nord Pas de Calais, France).

show abstract

Section: B Related Work and Paper Positioningmentioning

confidence: 99%

Section: B Related Work and Paper Positioningmentioning

confidence: 99%

A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework

Dotoli

Zgaya

Russo³

et al. 2017

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

show abstract

“…En [39] los agentes fueron utilizados para modelar y simular una compleja SC teniendo como objetivo minimizar los tiempos de espera y maximizar los ingresos. En [40] y [41] se describen plataformas basadas en agentes para la asignación de cargas en la red de transporte considerando condiciones ambientales que afectan el tiempo de viaje.…”

Section: Procesos Scor Y Agentes Inteligentesunclassified

Aplicaciones de inteligencia artificial en procesos de cadenas de suministros: una revisión sistemática

Ahumada

2016

Ingeniare. Rev. chil. ing.

View full text Add to dashboard Cite

RESUMENUna cadena de suministro (SC) es una red de empresas que producen, venden y entregan un producto o servicio a un segmento de mercado predeterminado. No solo incluye a los fabricantes y proveedores, sino que también a transportistas, almacenes, minoristas y los propios clientes, entre otros. Debido al avance tecnológico, específicamente en áreas como las comunicaciones, procesamiento computacional, gestión y almacenamiento de información, es posible apoyar a la administración de cadenas de suministros pudiendo hacerla mas eficiente. En este contexto, la inteligencia artificial (IA) ha sido aplicada en diferentes procesos de SC pero no hay conocimiento especifico sobre cuáles técnicas de IA están siendo aplicadas (o no) en los procesos de la SC o cuáles actividades de la SC están siendo apoyadas (o no) con técnicas de IA. Con base a lo anterior, el objetivo de este trabajo fue establecer de forma empírica el aporte de la IA en procesos de la SC, para luego establecer actividades de investigación a realizarse en el futuro. Para lograr esto, se realizó una revisión sistemática considerando el modelo SCOR como referencia para procesos de una SC. Los principales resultados indican que los algoritmos genéticos y los agentes inteligentes son las técnicas más investigadas para procesos de la SC relacionados con la planificación y, en menor medida, a procesos relacionados con la entrega de productos. Además, existe una tendencia a incluir la incertidumbre como trabajo futuro en diferentes técnicas de IA de manera que los modelos se acerquen más a la realidad.Palabras clave: Inteligencia artificial, modelo SCOR, revisión sistemática, cadena de suministros. ABSTRACT A supply chain (SC) is a network of companies that produce

show abstract

“…), we know that about $31.8 million of loans were provided to companies with carbon emission cap as collateral in 2017. Therefore, some scholars try to incorporate capital situation of the emission-dependent firms into their operational decision-making [8,9].Regarding the researches of 3PL firm, most scholars think that 3PL only provides logistics service for firms, which may include transportation and warehousing [10][11][12]. However, the increasing competition among 3PL firms leads to it must develop their own business scope.…”

mentioning

confidence: 99%

“…Regarding the researches of 3PL firm, most scholars think that 3PL only provides logistics service for firms, which may include transportation and warehousing [10][11][12]. However, the increasing competition among 3PL firms leads to it must develop their own business scope.…”

mentioning

confidence: 99%

Research on Operation and Financing Strategy of an Emission-Dependent Supply Chain under Variable Transportation Fee Strategy

Zhang

Yao

2019

Sustainability

View full text Add to dashboard Cite

Under the carbon cap-and-trade mechanism, we consider an emission-dependent supply chain consisting of a supplier, a manufacturer, and a 3PL firm that adopts variable transportation fee strategy. Five models on the basis of the supplier and manufacturer with or without capital constraints are considered to discuss members’ optimal decisions. The insights are obtained as follows. First, the ordering quantity under 3PL financing service is larger than that under two firms are well-funded when the transportation fee or carbon emission is less than a certain constant. The variable transportation fee strategy and members’ carbon emission reduction behavior are beneficial to each supply chain participant. Second, the carbon emissions of members decide whose capital constraint is more beneficial to 3PL firm, and 3PL prefers to cooperate with a medium rich manufacturer (rich supplier). Third, the external financing modes are analyzed to get the 3PL financing service can create new value for the manufacturer and 3PL if the transportation fee is below a threshold, and this threshold increases with the manufacturer’s carbon emission. When the transportation fee is larger than a threshold, a capital-constrained supplier will choose bank financing, and this threshold decreases with the supplier’s carbon emission. Finally, we demonstrate that the manufacturer’s loss aversion (carbon cap) can increase (decrease) its bankruptcy threshold.

show abstract

Route planning model of multi-agent system for a supply chain management

Cited by 19 publications

References 4 publications

A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework

A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework

Aplicaciones de inteligencia artificial en procesos de cadenas de suministros: una revisión sistemática

Research on Operation and Financing Strategy of an Emission-Dependent Supply Chain under Variable Transportation Fee Strategy

Contact Info

Product

Resources

About