Showing papers by "Adriana Giret published in 2017"

The Multi-agent Layer of CALMeD SURF

Abstract: This paper proposes a crowdsourcing approach that deals with the problem of Last Mile Delivery (LMD). The proposed approach is supported by Multi Agent System (MAS) techniques and makes use of a crowd of citizens that are moving in an urban area for their own needs. The idea is to employ those citizens to deliver parcels on their way to their destinations. The complexity of the approach lies in integrating the public infrastructure network of the city for the delivery route planning, and the citizens that are deliverers in the system with their own routes to their destinations. The proposed approach is supported by a MAS framework for open fleets management. Moreover, the executed tests suggest that the LMD by citizens can drastically reduce the emissions of carbon dioxide and other airborne pollutants that are caused by delivery trucks. Moreover it can reduce the traffic congestion and noise in urban areas.

Station Status Forecasting Module for a Multi-agent Proposal to Improve Efficiency on Bike-Sharing Usage

Abstract: Urban transportation involves a number of common problems: air and acoustic pollution, traffic jams, and so forth. This has become an important topic of study due to the interest in solving these issues in different areas (economical, social, ecological, etc.). Nowadays, one of the most popular urban transport systems are the shared vehicles systems. Among these systems there are the shared bicycle systems which have an special interest due to its characteristics. While solving some of the problems mentioned above, these systems also arise new problems such as the distribution of bicycles over time and space. Traditional approaches rely on the service provider to balancing the system, thus generating extra costs. Our proposal consists on an multi-agent system that includes user actions as a balancing mechanism, taking advantage of their trips to optimize the overall balance of the system. With this goal in mind the user is persuaded to deviate slightly from its origin/destination by providing appropriate arguments and incentives. This article presents the prediction module that will enable us to create such persuasive system. This module allow us to predict the demand for bicycles in the stations, forecasting the number of available parking spots (or available bikes). With this information the multi-agent system is capable of scoring alternative stations and routes and making offers to balance bikes across the stations. In order to achieve this, the most proper offers for the user will be predicted and used to persuade her.

A Multi-agent Approach to Implement a Reverse Production Virtual Market in Green Supply Chains

Abstract: The implementation of internal reverse production process programs often involves significant allocations of capital and resources for the construction and implementation of all the steps in the process. But, what if we think of reverse production process as a service-based manufacturing network, in which all the activities are outsourced and the only thing that a manufacturing company needs in order to participate is an interface/service to “play” in that ecosystem. In this work we present an approach to implement reverse production process following a Service-Oriented Manufacturing paradigm by means of a virtual market supported by intelligent software agents.

A Multi-agent Proposal for Efficient Bike-Sharing Usage

Abstract: Urban transportation systems have received a special interest in the last few years due to the necessity to reduce congestion, air pollution and acoustic contamination in today’s cities. Bike sharing systems have been proposed as an interesting solution to deal with these problems. Nevertheless, shared vehicle schemes also arise problems that must be addressed such as the vehicle distribution along time and across space in the city. Differently to classic approaches, we propose the architecture for a muti-agent system that tries to improve the efficiency of bike sharing systems by introducing user-driven balancing in the loop. The rationale is that of persuading users to slightly deviate from their origins/destinations by providing appropriate arguments and incentives, while optimizing the overall balance of the system. In this paper we present two of the proposed system’s modules. The first will allow us to predict bike demand in different stations. The second will score stations and alternative routes. This modules will be used to predict the most appropriate offers for users and try to persuade them.

A Multi-agent Approach for Composing Negotiation Items in a Reverse Logistic Virtual Market

Abstract: In this work a reverse production process is conceived as a service-based manufacturing network (ecosystem), in which the manufacturing companies “play” in the ecosystem by means of market services. One complex problem in a reverse logistic virtual market is the efficient composition and decomposition of the negotiation items. A negotiation item is defined as an item subject to be recycled: used products/scraps/wastes, a sub-part of a used product/scrap/waste, or the materials that are contained in the used product/scrap/waste. In this work we present a Multi-agent approach in order to compose the last two types of negotiation items from an orchestration of negotiation processes among the different stakeholders of the reverse logistic process (i.e. collecting points, recycling plants, disassembly plants, secondary material markets). In this way a call for buying, for example 10 tons of steel, can be handle in the virtual market as a complex process of buying and selling used products/scraps/wastes, or their sub-parts, in order to decompose and pre-process them (by recycling and/or disassembly plants) for extracting the steel contained in those items.