A multi-agent framework for load consolidation in logistics

Logistics companies mainly provide land transportation services facing with difficulties in making effective operational decisions. This is especially the case of making load/capacity/route planning and load consolidation where customer orders are generally unpredictable and subject to sudden changes. Classical modelling and decision support systems are mostly insufficient for providing satisfactory solutions in a reasonable time solving such dynamic problems. Agent-based approaches, especially multi-agent paradigms that can be considered as relatively new members of system science and software engineering, are providing effective mechanisms for modelling dynamic systems generally operating under unpredictable environments and having a high degree of complex interactions. It seems that multi-agent paradigms have big potential for handling complex problems in land transportation logistics. Based on this motivation, the paper proposes a multi-agent based framework for load consolidation problems of third-party logistics companies

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Selling Seeds, Selling Communities: Re-Seeing Agronomy and Conventional Agricultural Seed Development and Exchange in Rural Kansas and Missouri

This qualitative research explores agri-food issues in contemporary, conventional hybrid seed production and exchange, particularly the sales of high-earning corn and soy hybrids ubiquitous on the farms practicing conventional growing techniques in Northeast Kansas and Northwest Missouri. Data for this project is drawn from on-site interviews conducted with sales agronomists working in the NE Kansas and NW Missouri agricultural region. The project asks about the materiality of the hybrid seeds and how sales agronomists see, interact with, and describe seeds, chemicals, and other services to farmer clients. The research reveals a hybrid seed package that bears multiple meanings across different networks of individuals alongside agronomists, a population of non-farming rural community members who feel the losses in population and community resiliency associated with large-farm agriculture but who also feel committed and responsible to the individual wellbeing of their farmer clients. The research also reveals a growing prevalence of precision agriculture services offered by sales agronomists. Drawing from the work of Bennet’s vital materialism (2010) and contemporary revisions of the Deleuze-Guattarian assemblage (DeLanda 2016), this research suggests that automated precision agriculture methods reveal a food regime which distributes agency between many participants, conversely delimiting individual autonomy of the farmer-owner. I suggest that the problems preventing higher numbers of farmers from adopting ecologically sustainable practices may not be individually ideological or economic, but rather problems of agentic capacity, of who/what makes a difference in contemporary agricultural assemblages

TRIZ Future Conference 2004

TRIZ the Theory of Inventive Problem Solving is a living science and a practical methodology: millions of patents have been examined to look for principles of innovation and patterns of excellence. Large and small companies are using TRIZ to solve problems and to develop strategies for future technologies. The TRIZ Future Conference is the annual meeting of the European TRIZ Association, with contributions from everywhere in the world. The aims of the 2004 edition are the integration of TRIZ with other methodologies and the dissemination of systematic innovation practices even through SMEs: a broad spectrum of subjects in several fields debated with experts, practitioners and TRIZ newcomers

Nuclear Power

The world of the twenty first century is an energy consuming society. Due to increasing population and living standards, each year the world requires more energy and new efficient systems for delivering it. Furthermore, the new systems must be inherently safe and environmentally benign. These realities of today's world are among the reasons that lead to serious interest in deploying nuclear power as a sustainable energy source. Today's nuclear reactors are safe and highly efficient energy systems that offer electricity and a multitude of co-generation energy products ranging from potable water to heat for industrial applications. The goal of the book is to show the current state-of-the-art in the covered technical areas as well as to demonstrate how general engineering principles and methods can be applied to nuclear power systems

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse