Mitsuo Gen

Runwei Cheng

Lin Lin

Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

Multiobjective Genetic Algorithm Approach

Network Models and Optimization

Michael J. Spector

Mark V. Albert

Lemoyne S. Dunn

This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) Trends and future in learning and learning technologies expected in the next 10 years; (2) Technologies likely to have a significant impact on learning in the next 10 years; (3) Challenges that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) Reflections and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer interactions, information science, library science, and technology integration.

Bridging Human Intelligence and Artificial Intelligence

Jianfeng Lu

Based on first principle quantum mechanics, electronic structure theory is widely used in physics, chemistry, materials science, and related fields and has recently received increasing research attention in applied and computational mathematics. This book provides a self-contained, mathematically oriented introduction to the subject and its associated algorithms and analysis. It will help applied mathematics students and researchers with minimal background in physics understand the basics of electronic structure theory and prepare them to conduct research in this area. The book begins with an elementary introduction of quantum mechanics, including the uncertainty principle and the Hartree?Fock theory, which is considered the starting point of modern electronic structure theory. The authors then provide an in-depth discussion of two carefully selected topics that are directly related to several aspects of modern electronic structure calculations: density matrix based algorithms and linear response theory. Chapter 2 introduces the Kohn?Sham density functional theory with a focus on the density matrix based numerical algorithms, and Chapter 3 introduces linear response theory, which provides a unified viewpoint of several important phenomena in physics and numerics. An understanding of these topics will prepare readers for more advanced topics in this field. The book concludes with the random phase approximation to the correlation energy. The book is written for advanced undergraduate and beginning graduate students, specifically those with mathematical backgrounds but without a priori knowledge of quantum mechanics, and can be used for self-study by researchers, instructors, and other scientists. The book can also serve as a starting point to learn about many-body perturbation theory, a topic at the frontier of the study of interacting electrons.

A Mathematical Introduction to Electronic Structure Theory

J. Michael Spector

There are two distinct professional communities that share an interest in using innovative approaches and emerging technologies to design and implement effective support for learning. This edited collection addresses the growing divide between the learning sciences community and the instructional design and technology community, bringing leading scholars from both fields together in one volume in an attempt to find productive middle ground. Chapters discuss the implications of not bridging this divide, propose possible resolutions, and go on to lay a foundation for continued discourse in this important area.

Constructive Articulation Between Communities

The Sciences of Learning and Instructional Design

This book explores, analyzes, and compares the use of German and Chinese demonstratives. Discourse and textual uses of the forms are considered, as well as their locative and temporal uses. The author observes that in both languages the demonstratives can be used to refer to referents. However, she departs from the common assumption that proximal demonstratives refer to entities or places close to the speaker, while non-proximal demonstratives refer to entities or places far from the speaker. Having analyzed a representative sampling consisting of a German text and a Chinese text, the author argues that both German and Chinese proximal demonstratives can signal the meaning of HIGH DEIXIS in a system of DEIXIS in the Columbia School of linguistics framework, whereas their non-proximal demonstratives can signal the meaning of LOW DEIXIS. In addition, Chinese demonstratives can be used under more circumstances than German demonstratives due to the lack of articles in Chinese. The author also argues that Cognitive Linguistic analysis is more helpful for new language learners, whereas the Columbia School of linguistics may be better suited to advanced learners who wish to know more about the intrinsic differences between words with similar meanings and uses. This book aims to help German learners better understand the German reference system. Readers with a Chinese language background will definitely benefit more from the book, as well as Chinese learners with a German language background. For pure linguistic enthusiasts and multi-linguals, the book offers an extensive introduction to the Columbia School of linguistics, and can open a new horizon for learning a new language comparatively.

Lin Lin

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