The Multi-agent Layer of CALMeD SURF

Rebollo, Miguel; Giret, Adriana; Carrascosa, Carlos; Julián, Vicente

doi:10.1007/978-3-030-01713-2_31

Cited by 6 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Giret et al [ 15 ] and Rebollo et al [ 29 ], multi-agent systems are combined with complex network-based algorithms to route parcels through the crowd. The proposed system maintains live information about the city’s transportation network and the couriers’ GPS locations.…”

Section: Related Workmentioning

confidence: 99%

“…However, in practice unexpected events can interfere with the plan execution. To react to unexpected events and plan deviations, at least the incorporation of live data is necessary, as proposed by Giret et al [ 15 ] and Rebollo et al [ 29 ]. While transfer methods based on live data already have great advantages over offline methods, they can at most be reactive.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing

Bruns¹,

Dötterl²,

Dunkel³

et al. 2023

Sensors

View full text Add to dashboard Cite

Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who struggle to complete those tasks successfully, resulting in high failure rates and low service quality. A promising solution to ensure higher quality of service is to continuously adapt the assignment and respond to failure-causing events by transferring tasks to better-suited workers who use different routes or vehicles. However, implementing task transfers in mobile crowdsourcing is difficult because workers are autonomous and may reject transfer requests. Moreover, task outcomes are uncertain and need to be predicted. In this paper, we propose different mechanisms to achieve outcome prediction and task coordination in mobile crowdsourcing. First, we analyze different data stream learning approaches for the prediction of task outcomes. Second, based on the suggested prediction model, we propose and evaluate two different approaches for task coordination with different degrees of autonomy: an opportunistic approach for crowdshipping with collaborative, but non-autonomous workers, and a market-based model with autonomous workers for crowdsensing.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing

Bruns¹,

Dötterl²,

Dunkel³

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Crowdshipping can save companies money -as they no longer need to set up a carrier structureand can be a new source of income for many people. Our approach is named CALMeD SURF [9] and is based on crowdsourcing, taking advantage of the movements of the citizens in the urban area, that move for their own needs. This application is addressed as a mobile phone app for: customers that want to deliver a parcel, and users that want to serve as occasional deliverers in an urban area.…”

Section: A Case Study: Last Mile Delivery a Crowd Logistic Approachmentioning

confidence: 99%

How to Choose the Greenest Delivery Plan: A Framework to Measure Key Performance Indicators for Sustainable Urban Logistics

Giret

Julián

Corchado

et al. 2018

Advances in Production Management Systems. Smart Manufacturing for Industry 4.0

View full text Add to dashboard Cite

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

show abstract

“…In [6], parcels are exchanged between couriers, but according to a plan that is computed offline. In [15,25] parcels are exchanged between couriers based on live information about the city's transportation network and the couriers' GPS locations. Some related work considers temporal aspects in crowdshipping, e.g., the couriers' temporal availability [4,6].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Crowdshipping Systems with Agent-Based Simulation

Dötterl

Bruns

Dunkel

et al. 2020

Multi-Agent Systems and Agreement Technologies

View full text Add to dashboard Cite

In parcel delivery, the "last mile" from the parcel hub to the customer is costly, especially for time-sensitive delivery tasks that have to be completed within hours after arrival. Recently, crowdshipping has attracted increased attention as a new alternative to traditional delivery modes. In crowdshipping, private citizens ("the crowd") perform short detours in their daily lives to contribute to parcel delivery in exchange for small incentives. However, achieving desirable crowd behavior is challenging as the crowd is highly dynamic and consists of autonomous, self-interested individuals. Leveraging crowdshipping for time-sensitive deliveries remains an open challenge. In this paper, we present an agent-based approach to on-time parcel delivery with crowds. Our system performs data stream processing on the couriers' smartphone sensor data to predict delivery delays. Whenever a delay is predicted, the system attempts to forge an agreement for transferring the parcel from the current deliverer to a more promising courier nearby. Our experiments show that through accurate delay predictions and purposeful task transfers many delays can be prevented that would occur without our approach.

show abstract

The Multi-agent Layer of CALMeD SURF

Cited by 6 publications

References 11 publications

Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing

Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing

How to Choose the Greenest Delivery Plan: A Framework to Measure Key Performance Indicators for Sustainable Urban Logistics

Evaluating Crowdshipping Systems with Agent-Based Simulation

Contact Info

Product

Resources

About