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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. [ABSTRACT FROM AUTHOR]

Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost, and quality as optimization objectives. Currently, energy-efficiency is also taken into consideration in these problems. However, this problem is NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the Job-shop Scheduling Problem in which machines can consume different amounts of energy to process tasks at different rates (speed scaling). This problem 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 evaluation section shows that a powerful commercial tool for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality. [ABSTRACT FROM AUTHOR]

Due to the increase in collaborative work and the decentralization of processes in many domains, there is an expanding demand for large-scale, flexible and adaptive software systems to support the interactions of people and institutions distributed in heterogeneous environments. Commonly, these software applications should follow specific regulations meaning the actors using them are bound by rights, duties and restrictions. Since this normative environment determines the final design of the software system, it should be considered as an important issue during the design of the system. Some agent-oriented software engineering methodologies deal with the development of normative systems (systems that have a normative environment) by integrating the analysis of the normative environment of a system in the development process. This paper analyses to what extent these methodologies support the analysis and formalisation of the normative environment and highlights some open issues of the topic. [ABSTRACT FROM AUTHOR]

This paper presents a MAS-based infrastructure for the specification of a negotiation framework that handles multiple negotiation protocols in a coherent and flexible way. Although it may be used to implement one single type of agreement mechanism, it has been designed in such a way that multiple mechanisms may be available at any given time, to be activated and tailored on demand (on-line) by participating agents. The framework is also generic enough so that new protocols may be easily added. This infrastructure has been successfully used in a case study to implement a simulation tool as a component of a larger framework based on an electronic market of water rights. [ABSTRACT FROM AUTHOR]

Today, the need for architectures and computational models for large-scale open multi-agent systems is considered to be a key issue for the success of agent technology in real-world scenarios. This paper analyzes the significant unsolved problems that must be taken into account in order to develop real, open multi-agent systems. It identifies requirements and related open issues, discusses how some of these requirements have been tackled by current technologies, and explains how the THOMAS architecture is able to give support to these open issues. This paper also describes the THOMAS abstract architecture and computational model for large-scale open multi-agent systems based on a service-oriented approach that specifically addresses the design of virtual organizations. An application example for the management of a travel agency system, which demonstrates the new features of the proposal, is also presented. [ABSTRACT FROM AUTHOR]

In recent years the development of automated traffic systems has been gaining increasing attention, and a substantial amount of effort has been invested in trying to find a solution to problems associated to road transport. Among these problems are road accidents caused by human-related factors, such as tiredness, loss of control, a slow reaction time, limited field of view, etc. Another transport-related problem is that of loss of time which may be caused by a slow driving speed due to weather conditions, road conditions, visibility, traffic congestion, etc. In this paper, we present a distributed architecture and the underline distributed algorithm for solving the global road transportation system, which is being developed by several European Universities. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]