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Dr. Adriana Giret
Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Valencia, Spain

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Research Keywords & Expertise

0 multiagent systems
0 Intelligent manufacturing systems
0 Agent-supported simulation for manufacturing systems
0 Applications of multiagent systems
0 Sustainable intelligent manufacturing and logistics systems

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multiagent systems
Intelligent manufacturing systems
Agent-supported simulation for manufacturing systems
Sustainable intelligent manufacturing and logistics systems

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Review articles
Published: 02 April 2021 in Journal of Computing and Information Science in Engineering
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With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

ACS Style

Maria Gabriela Juarez Juarez; Vicente Juan Botti; Adriana S. Giret. Digital Twins: Review and Challenges. Journal of Computing and Information Science in Engineering 2021, 21, 1 -32.

AMA Style

Maria Gabriela Juarez Juarez, Vicente Juan Botti, Adriana S. Giret. Digital Twins: Review and Challenges. Journal of Computing and Information Science in Engineering. 2021; 21 (3):1-32.

Chicago/Turabian Style

Maria Gabriela Juarez Juarez; Vicente Juan Botti; Adriana S. Giret. 2021. "Digital Twins: Review and Challenges." Journal of Computing and Information Science in Engineering 21, no. 3: 1-32.

Editorial
Published: 21 August 2019 in Service Oriented Computing and Applications
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CO2-free urban logistics is one of the 10 objectives to reach by 2030 as part of transport policy. What technologies can help to accomplish it? In this paper, we discuss the very complex situation that today’s big and modern cities are facing with a tremendous environment of many urban logistics companies running in the same city. In the majority of cases, there is less or none coordination among them worsening traffic congestions. We believe that intelligent techniques are one of the key approaches that can aid to support smart and sustainable urban logistic applications. There are large open problems in the field of cooperative urban logistics that can greatly improve with the help of artificial intelligence. Some solutions are cited in this paper, but the overall conclusion is that there is still much work to be done.

ACS Style

Adriana Giret. Smart and sustainable urban logistic applications aided by intelligent techniques. Service Oriented Computing and Applications 2019, 13, 185 -186.

AMA Style

Adriana Giret. Smart and sustainable urban logistic applications aided by intelligent techniques. Service Oriented Computing and Applications. 2019; 13 (3):185-186.

Chicago/Turabian Style

Adriana Giret. 2019. "Smart and sustainable urban logistic applications aided by intelligent techniques." Service Oriented Computing and Applications 13, no. 3: 185-186.

Conference paper
Published: 03 August 2019 in Econometrics for Financial Applications
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Optimized urban logistics is an important issue for rapidly growing cities worldwide. Many criteria can be optimized in order to improve the performance of urban logistics. Economic and time dependent criteria are central but not the only ones; lately, sustainable criteria are becoming key and urgent due to new regulations and environmental concern of governments and the society. In this work we review the state of the art of intelligent developments and techniques that might aid to build smart and optimized urban logistic applications. Moreover, we propose a prototype platform conceived as a supporting and facilitating layer for the growing business of last mile delivery (LMD) companies that operate in cities in an isolated way. Our vision is to provide a cooperative intelligent platform that provides coordination and collaboration services for the LMD companies of urban areas.

ACS Style

Adriana Giret; Vicente Julián; Vicente Botti. An Intelligent Platform for Supporting Optimized Collaborative Urban Logistics. Econometrics for Financial Applications 2019, 3 -14.

AMA Style

Adriana Giret, Vicente Julián, Vicente Botti. An Intelligent Platform for Supporting Optimized Collaborative Urban Logistics. Econometrics for Financial Applications. 2019; ():3-14.

Chicago/Turabian Style

Adriana Giret; Vicente Julián; Vicente Botti. 2019. "An Intelligent Platform for Supporting Optimized Collaborative Urban Logistics." Econometrics for Financial Applications , no. : 3-14.

Journal article
Published: 31 May 2019 in Sustainability
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Nowadays, the manufacturing industry faces the challenge of reducing energy consumption and the associated environmental impacts. Production scheduling is an effective approach for energy-savings management. During the entire workshop production process, both the processing and transportation operations consume large amounts of energy. To reduce energy consumption, an energy-efficient job-shop scheduling problem (EJSP) with transportation constraints was proposed in this paper. First, a mixed-integer programming model was established to minimize both the comprehensive energy consumption and makespan in the EJSP. Then, an enhanced estimation of distribution algorithm (EEDA) was developed to solve the problem. In the proposed algorithm, an estimation of distribution algorithm was employed to perform the global search and an improved simulated annealing algorithm was designed to perform the local search. Finally, numerical experiments were implemented to analyze the performance of the EEDA. The results showed that the EEDA is a promising approach and that it can solve EJSP effectively and efficiently.

ACS Style

Min Dai; Ziwei Zhang; Adriana Giret; Miguel A. Salido. An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints. Sustainability 2019, 11, 3085 .

AMA Style

Min Dai, Ziwei Zhang, Adriana Giret, Miguel A. Salido. An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints. Sustainability. 2019; 11 (11):3085.

Chicago/Turabian Style

Min Dai; Ziwei Zhang; Adriana Giret; Miguel A. Salido. 2019. "An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints." Sustainability 11, no. 11: 3085.

Journal article
Published: 19 February 2019 in Energies
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This work proposes a persuasion model based on argumentation theory and users’ characteristics for improving the use of resources in bike sharing systems, fostering the use of the bicycles and thus contributing to greater energy sustainability by reducing the use of carbon-based fuels. More specifically, it aims to achieve a balanced network of pick-up and drop-off stations in urban areas with the help of the users, thus reducing the dedicated management trucks that redistribute bikes among stations. The proposal aims to persuade users to choose different routes from the shortest route between a start and an end location. This persuasion is carried out when it is not possible to park the bike in the desired station due to the lack of parking slots, or when the user is highly influenceable. Differently to other works, instead of employing a single criteria to recommend alternative stations, the proposed system can incorporate a variety of criteria. This result is achieved by providing a defeasible logic-based persuasion engine that is capable of aggregating the results from multiple recommendation rules. The proposed framework is showcased with an example scenario of a bike sharing system.

ACS Style

Carlos Diez; Javier Palanca; Victor Sanchez-Anguix; Stella Heras; Adriana Giret; Vicente Julián. Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach. Energies 2019, 12, 662 .

AMA Style

Carlos Diez, Javier Palanca, Victor Sanchez-Anguix, Stella Heras, Adriana Giret, Vicente Julián. Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach. Energies. 2019; 12 (4):662.

Chicago/Turabian Style

Carlos Diez; Javier Palanca; Victor Sanchez-Anguix; Stella Heras; Adriana Giret; Vicente Julián. 2019. "Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach." Energies 12, no. 4: 662.

Journal article
Published: 16 January 2019 in Sustainability
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With increasingly stringent environmental regulations on emission standards, enterprises and investigators are looking for effective ways to decrease GHG emission from products. As an important method for reducing GHG emission of products, low-carbon product family design has attracted more and more attention. Existing research, related to low-carbon product family design, did not take into account remanufactured products. Nowadays, it is popular to launch remanufactured products for environmental benefit and meeting customer needs. On the one hand, the design of remanufactured products is influenced by product family design. On the other hand, the launch of remanufactured products may cannibalize the sale of new products. Thus, the design of remanufactured products should be considered together with the product family design for obtaining the maximum profit and reducing the GHG emission as soon as possible. The purpose of this paper is to present an optimization model to concurrently determine product family design, remanufactured products planning and remanufacturing parameters selection with consideration of the customer preference, the total profit of a company and the total GHG emission from production. A genetic algorithm is applied to solve the optimization problem. The proposed method can help decision-makers to simultaneously determine the design of a product family and remanufactured products with a better trade-off between profit and environmental impact. Finally, a case study is performed to demonstrate the effectiveness of the presented approach.

ACS Style

Qi Wang; Dunbing Tang; Shipei Li; Jun Yang; Miguel A. Salido; Adriana Giret; Haihua Zhu. An Optimization Approach for the Coordinated Low-Carbon Design of Product Family and Remanufactured Products. Sustainability 2019, 11, 460 .

AMA Style

Qi Wang, Dunbing Tang, Shipei Li, Jun Yang, Miguel A. Salido, Adriana Giret, Haihua Zhu. An Optimization Approach for the Coordinated Low-Carbon Design of Product Family and Remanufactured Products. Sustainability. 2019; 11 (2):460.

Chicago/Turabian Style

Qi Wang; Dunbing Tang; Shipei Li; Jun Yang; Miguel A. Salido; Adriana Giret; Haihua Zhu. 2019. "An Optimization Approach for the Coordinated Low-Carbon Design of Product Family and Remanufactured Products." Sustainability 11, no. 2: 460.

Conference paper
Published: 12 December 2018 in Artificial Intelligence: Foundations, Theory, and Algorithms
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Within the emerging industrial sustainability domain, production efficiency interventions are gaining practical interest since manufacturing plants are facing increasing pressure to reduce their carbon footprint, driven by concerns related to energy costs and climate changes. This work focuses on the challenging issue of energy aware production scheduling and rescheduling systems (EAPSRS). The proposed multi-agent architecture (MA-EAPSRS) is hybrid, combining the predictive and the reactive phase while taking into account sustainability in both parts. It is composed of two cooperating multi-agent systems: the first one represents the smart manufacturing plant and the second one is the smart energy supply plant. It is based on interactions and negotiations between factory schedulers and energy providers. Uncertainties in term of machine’s disruptions and variation of processing time and in term of energy availability are also considered. In order to assess the proposed approach, an illustrative case study addressing the problem is presented and discussed.

ACS Style

Maroua Nouiri; Damien Trentesaux; Abdelghani Bekrar; Adriana Giret; Miguel A. Salido. Cooperation Between Smart Manufacturing Scheduling Systems and Energy Providers: A Multi-agent Perspective. Artificial Intelligence: Foundations, Theory, and Algorithms 2018, 197 -210.

AMA Style

Maroua Nouiri, Damien Trentesaux, Abdelghani Bekrar, Adriana Giret, Miguel A. Salido. Cooperation Between Smart Manufacturing Scheduling Systems and Energy Providers: A Multi-agent Perspective. Artificial Intelligence: Foundations, Theory, and Algorithms. 2018; ():197-210.

Chicago/Turabian Style

Maroua Nouiri; Damien Trentesaux; Abdelghani Bekrar; Adriana Giret; Miguel A. Salido. 2018. "Cooperation Between Smart Manufacturing Scheduling Systems and Energy Providers: A Multi-agent Perspective." Artificial Intelligence: Foundations, Theory, and Algorithms , no. : 197-210.

Journal article
Published: 03 December 2018 in Sustainability
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Sustainable transportation is one of the major concerns in cities. This concern involves all type of movements motivated by different goals (mobility of citizens, transportation of goods and parcels, etc.). The main goal of this work is to provide an intelligent approach for Sustainable Last Mile Delivery, by reducing (or even deleting) the need of dedicated logistic moves (by cars, and/or trucks). The method attempts to reduce the number of movements originated by the parcels delivery by taking advantage of the citizens’ movements. In this way our proposal follows a crowdsourcing approach, in which the citizens that moves in the city, because of their own needs, become temporal deliverers. The technology behind our approach relays on Multi-agent System techniques and complex network-based algorithms for optimizing sustainable delivery routes. These artificial intelligent approaches help to reduce the complexity of the scenario providing an efficient way to integrate the citizens’ routes that can be executed using the different transportation means and networks available in the city (public system, private transportation, eco-vehicles sharing systems, etc.). A complex network-based algorithm is used for computing and proposing an optimized Sustainable Last Mile Delivery route to the crowd. Moreover, the executed tests show the feasibility of the proposed solution, together with a high reduction of the CO 2 emission coming from the delivery trucks that, in the case studies, are no longer needed for delivery.

ACS Style

Adriana Giret; Carlos Carrascosa; Vicente Julian; Miguel Rebollo; Vicente Botti. A Crowdsourcing Approach for Sustainable Last Mile Delivery. Sustainability 2018, 10, 4563 .

AMA Style

Adriana Giret, Carlos Carrascosa, Vicente Julian, Miguel Rebollo, Vicente Botti. A Crowdsourcing Approach for Sustainable Last Mile Delivery. Sustainability. 2018; 10 (12):4563.

Chicago/Turabian Style

Adriana Giret; Carlos Carrascosa; Vicente Julian; Miguel Rebollo; Vicente Botti. 2018. "A Crowdsourcing Approach for Sustainable Last Mile Delivery." Sustainability 10, no. 12: 4563.

Regular paper
Published: 13 November 2018 in International Journal of Precision Engineering and Manufacturing
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New stricter environmental regulations and consumer rising issues are making greenhouse gases (GHG) emission an increasing and urgent concern for manufacturing companies. Companies and researchers are seeking appropriate methods to reduce GHG emission of the manufactured products. Previous studies on low-carbon product design mainly concern on a single product. Currently, it is common to design a product family instead of a single product for increasing varieties to satisfy customers’ requirements. Owing to the difference in design methods, the low-carbon design method for a single product cannot handle a product family. In addition, nowadays, the sourcing strategy is widely adopted by companies. A key problem of the procurement is supplier selection. The supplier selection affects not only profit but also GHG emission. However, it has not been simultaneously considered in low-carbon product design. In this article, an optimization model for coordinating low-carbon design of product family and supplier selection is proposed. In the model, the profit and the GHG emission of a product family are taken into consideration at the same time. Moreover, a genetic algorithm is developed to solve the established model. Finally, a case study is performed to verify the validity of the proposed approach.

ACS Style

Qi Wang; Dunbing Tang; Leilei Yin; Inayat Ullah; Miguel A. Salido; Adriana Giret. An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family. International Journal of Precision Engineering and Manufacturing 2018, 19, 1715 -1726.

AMA Style

Qi Wang, Dunbing Tang, Leilei Yin, Inayat Ullah, Miguel A. Salido, Adriana Giret. An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family. International Journal of Precision Engineering and Manufacturing. 2018; 19 (11):1715-1726.

Chicago/Turabian Style

Qi Wang; Dunbing Tang; Leilei Yin; Inayat Ullah; Miguel A. Salido; Adriana Giret. 2018. "An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family." International Journal of Precision Engineering and Manufacturing 19, no. 11: 1715-1726.

Conference paper
Published: 14 October 2018 in Transactions on Petri Nets and Other Models of Concurrency XV
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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.

ACS Style

C. Diez; V. Sanchez-Anguix; J. Palanca; V. Julian; A. Giret. Station Status Forecasting Module for a Multi-agent Proposal to Improve Efficiency on Bike-Sharing Usage. Transactions on Petri Nets and Other Models of Concurrency XV 2018, 476 -489.

AMA Style

C. Diez, V. Sanchez-Anguix, J. Palanca, V. Julian, A. Giret. Station Status Forecasting Module for a Multi-agent Proposal to Improve Efficiency on Bike-Sharing Usage. Transactions on Petri Nets and Other Models of Concurrency XV. 2018; ():476-489.

Chicago/Turabian Style

C. Diez; V. Sanchez-Anguix; J. Palanca; V. Julian; A. Giret. 2018. "Station Status Forecasting Module for a Multi-agent Proposal to Improve Efficiency on Bike-Sharing Usage." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 476-489.

Conference paper
Published: 14 October 2018 in Privacy Enhancing Technologies
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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.

ACS Style

Adriana Giret; Adrian Martinez; Vicente Botti. A Multi-agent Approach for Composing Negotiation Items in a Reverse Logistic Virtual Market. Privacy Enhancing Technologies 2018, 417 -430.

AMA Style

Adriana Giret, Adrian Martinez, Vicente Botti. A Multi-agent Approach for Composing Negotiation Items in a Reverse Logistic Virtual Market. Privacy Enhancing Technologies. 2018; ():417-430.

Chicago/Turabian Style

Adriana Giret; Adrian Martinez; Vicente Botti. 2018. "A Multi-agent Approach for Composing Negotiation Items in a Reverse Logistic Virtual Market." Privacy Enhancing Technologies , no. : 417-430.

Conference paper
Published: 14 October 2018 in Transactions on Petri Nets and Other Models of Concurrency XV
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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.

ACS Style

M. Rebollo; A. Giret; C. Carrascosa; V. Julian. The Multi-agent Layer of CALMeD SURF. Transactions on Petri Nets and Other Models of Concurrency XV 2018, 446 -460.

AMA Style

M. Rebollo, A. Giret, C. Carrascosa, V. Julian. The Multi-agent Layer of CALMeD SURF. Transactions on Petri Nets and Other Models of Concurrency XV. 2018; ():446-460.

Chicago/Turabian Style

M. Rebollo; A. Giret; C. Carrascosa; V. Julian. 2018. "The Multi-agent Layer of CALMeD SURF." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 446-460.

Conference paper
Published: 25 August 2018 in Security Education and Critical Infrastructures
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The sustainability of urban logistics is an important issue for rapidly growing cities worldwide. Although many cities and research works have developed strategies to move people more efficiently and safely within the urban environment, much less attention has been paid to the importance of optimizing the delivery of goods to people at work and home taking into account sustainable goals. In this work we propose a framework that aids to register and measure a set of sustainable Key Performance Indicators (KPIs) for delivery routes and plans in urban zones. The approach is general and based on a set of well defined KPIs from the specialized research field.

ACS Style

Adriana Giret; Vicente Julián; Juan Manuel Corchado; Alberto Fernández; Miguel A. Salido; Dunbing Tang. How to Choose the Greenest Delivery Plan: A Framework to Measure Key Performance Indicators for Sustainable Urban Logistics. Security Education and Critical Infrastructures 2018, 181 -189.

AMA Style

Adriana Giret, Vicente Julián, Juan Manuel Corchado, Alberto Fernández, Miguel A. Salido, Dunbing Tang. How to Choose the Greenest Delivery Plan: A Framework to Measure Key Performance Indicators for Sustainable Urban Logistics. Security Education and Critical Infrastructures. 2018; ():181-189.

Chicago/Turabian Style

Adriana Giret; Vicente Julián; Juan Manuel Corchado; Alberto Fernández; Miguel A. Salido; Dunbing Tang. 2018. "How to Choose the Greenest Delivery Plan: A Framework to Measure Key Performance Indicators for Sustainable Urban Logistics." Security Education and Critical Infrastructures , no. : 181-189.

Conference paper
Published: 25 August 2018 in Security Education and Critical Infrastructures
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Advance in applied scheduling is a source of innovation in the manufacturing field, where new results help industrial practitioners in production management. The literature of rescheduling problems for single-objective optimization is well study, while there is a lack of extensive studies for the case of rescheduling for multi-objective optimization, especially for energy aware scheduling. This paper extends a previous work over an energy aware scheduling problem, modelled from a real industrial case study, extending its manufacturing environment to a dynamic one. To this end, two rescheduling techniques are developed to tackle machines disruptions (greedy-heuristic and meta-heuristic). They are compared to existing approach thought manufacturing environment simulations. The results give insight to improve the production management in terms of rescheduling quality and computational time.

ACS Style

Sergio Ferrer; Giancarlo Nicolò; Miguel A. Salido; Adriana Giret; Federico Barber. Dynamic Rescheduling in Energy-Aware Unrelated Parallel Machine Problems. Security Education and Critical Infrastructures 2018, 232 -240.

AMA Style

Sergio Ferrer, Giancarlo Nicolò, Miguel A. Salido, Adriana Giret, Federico Barber. Dynamic Rescheduling in Energy-Aware Unrelated Parallel Machine Problems. Security Education and Critical Infrastructures. 2018; ():232-240.

Chicago/Turabian Style

Sergio Ferrer; Giancarlo Nicolò; Miguel A. Salido; Adriana Giret; Federico Barber. 2018. "Dynamic Rescheduling in Energy-Aware Unrelated Parallel Machine Problems." Security Education and Critical Infrastructures , no. : 232-240.

Chapter
Published: 30 June 2018 in Sustainable Manufacturing and Remanufacturing Management
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Many real-world problems are known as planning and scheduling problems, where resources must be allocated so as to optimize overall performance objectives. The traditional scheduling models consider performance indicators such as processing time, cost, and quality as optimization objectives. However, most of them do not take into account energy consumption and robustness. We focus our attention in a job-shop scheduling problem where machines can work at different speeds. It represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine, and this machine can work at different speeds. The main goal of the paper is focused on the analysis of three important objectives: energy efficiency, robustness, and makespan, and the relationship among them. We present some analytical formulas to estimate the ratio/relationship between these parameters. It can be observed that there exist a clear relationship between robustness and energy efficiency and a clear trade-off between robustness/energy efficiency and makespan. It represents an advance in the state of the art of production scheduling, so obtaining energy-efficient solutions also supposes obtaining robust solutions, and vice versa.

ACS Style

M. A. Salido; J. Escamilla; Federico Barber; A. Giret; D. B. Tang; M. Dai. Energy Efficiency, Robustness, and Makespan Optimality in Job-Shop Scheduling Problems. Sustainable Manufacturing and Remanufacturing Management 2018, 213 -233.

AMA Style

M. A. Salido, J. Escamilla, Federico Barber, A. Giret, D. B. Tang, M. Dai. Energy Efficiency, Robustness, and Makespan Optimality in Job-Shop Scheduling Problems. Sustainable Manufacturing and Remanufacturing Management. 2018; ():213-233.

Chicago/Turabian Style

M. A. Salido; J. Escamilla; Federico Barber; A. Giret; D. B. Tang; M. Dai. 2018. "Energy Efficiency, Robustness, and Makespan Optimality in Job-Shop Scheduling Problems." Sustainable Manufacturing and Remanufacturing Management , no. : 213-233.

Conference paper
Published: 20 June 2018 in Communications in Computer and Information Science
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Nowadays, the need of Intelligent Transportation Systems software tools and services for Sustainable Transportation is urgent. This paper proposes an ontology specially tailored for Intelligent Transportation System characterization. The main features of the proposed ontology is the ability to incorporate sustainable variables when characterizing a transportation system, and the coverage of open fleet concepts together with its dynamic features. Moreover, it is enhanced to facilitate its integration with other intelligent components that in a wider and complete application tool can provide intelligent computation over the data specified with the proposed ontology.

ACS Style

Adriana Giret; Vicente Julian; Carlos Carrascosa; Miguel Rebollo. An Ontology for Sustainable Intelligent Transportation Systems. Communications in Computer and Information Science 2018, 381 -391.

AMA Style

Adriana Giret, Vicente Julian, Carlos Carrascosa, Miguel Rebollo. An Ontology for Sustainable Intelligent Transportation Systems. Communications in Computer and Information Science. 2018; ():381-391.

Chicago/Turabian Style

Adriana Giret; Vicente Julian; Carlos Carrascosa; Miguel Rebollo. 2018. "An Ontology for Sustainable Intelligent Transportation Systems." Communications in Computer and Information Science , no. : 381-391.

Conference paper
Published: 20 June 2018 in Communications in Computer and Information Science
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Nowadays, the advance of the technology has allowed to develop applications and systems to facilitate the daily life of the people. One of the most used field by thousands of people every day is to generate routes to go from one place to another, obtaining not only the route according to the means of transport that the user selects, but also can get recommendations of places of interest that can be found along the way. Unfortunately, these applications do not consider the profile of the end users, and generate the same routes for a person who has a disability as for those who do not. In this article, we propose a model to create a recommendation system based on the user profile to generate automatic and personalized routes on foot or on public transportation for people with disabilities.

ACS Style

Andrea Peralta Bravo; Adriana Giret. Recommender System of Walking or Public Transportation Routes for Disabled Users. Communications in Computer and Information Science 2018, 392 -403.

AMA Style

Andrea Peralta Bravo, Adriana Giret. Recommender System of Walking or Public Transportation Routes for Disabled Users. Communications in Computer and Information Science. 2018; ():392-403.

Chicago/Turabian Style

Andrea Peralta Bravo; Adriana Giret. 2018. "Recommender System of Walking or Public Transportation Routes for Disabled Users." Communications in Computer and Information Science , no. : 392-403.

Journal article
Published: 01 November 2017 in Journal of Cleaner Production
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ACS Style

Adriana Giret; Damien Trentesaux; Miguel A. Salido; Emilia Garcia; Emmanuel Adam. A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems. Journal of Cleaner Production 2017, 167, 1370 -1386.

AMA Style

Adriana Giret, Damien Trentesaux, Miguel A. Salido, Emilia Garcia, Emmanuel Adam. A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems. Journal of Cleaner Production. 2017; 167 ():1370-1386.

Chicago/Turabian Style

Adriana Giret; Damien Trentesaux; Miguel A. Salido; Emilia Garcia; Emmanuel Adam. 2017. "A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems." Journal of Cleaner Production 167, no. : 1370-1386.

Conference paper
Published: 29 August 2017 in New Approaches for Security, Privacy and Trust in Complex Environments
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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.

ACS Style

Adriana Giret; Miguel A. Salido. A Multi-agent Approach to Implement a Reverse Production Virtual Market in Green Supply Chains. New Approaches for Security, Privacy and Trust in Complex Environments 2017, 399 -407.

AMA Style

Adriana Giret, Miguel A. Salido. A Multi-agent Approach to Implement a Reverse Production Virtual Market in Green Supply Chains. New Approaches for Security, Privacy and Trust in Complex Environments. 2017; ():399-407.

Chicago/Turabian Style

Adriana Giret; Miguel A. Salido. 2017. "A Multi-agent Approach to Implement a Reverse Production Virtual Market in Green Supply Chains." New Approaches for Security, Privacy and Trust in Complex Environments , no. : 399-407.

Conference paper
Published: 03 March 2017 in Econometrics for Financial Applications
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The aim of this paper is to study a set of emerging key-enabling requirements for the design of multi-agent or holonic manufacturing systems dealing with the energy aware scheduling of future production systems. These requirements are organized according to three different views, namely informational, organizational and lifecycle views. It is shown that these emerging key-enabling requirements are not sufficiently addressed by the research literature. An illustrative futuristic example of a system complying with these requirements is provided. From this example, new research opportunities and issues can be easily found.

ACS Style

Damien Trentesaux; Adriana Giret; Flavio Tonelli; Petr Skobelev. Emerging Key Requirements for Future Energy-Aware Production Scheduling Systems: A Multi-agent and Holonic Perspective. Econometrics for Financial Applications 2017, 127 -141.

AMA Style

Damien Trentesaux, Adriana Giret, Flavio Tonelli, Petr Skobelev. Emerging Key Requirements for Future Energy-Aware Production Scheduling Systems: A Multi-agent and Holonic Perspective. Econometrics for Financial Applications. 2017; ():127-141.

Chicago/Turabian Style

Damien Trentesaux; Adriana Giret; Flavio Tonelli; Petr Skobelev. 2017. "Emerging Key Requirements for Future Energy-Aware Production Scheduling Systems: A Multi-agent and Holonic Perspective." Econometrics for Financial Applications , no. : 127-141.