This book introduces multiple criteria and multiple constraint levels linear programming (MC2LP), which is an extension of linear programming (LP) and multiple criteria linear programming (MCLP). In the last decade, the author and a group of researchers from the USA, China, Korea, Germany, and Hungary have been working on the theory and applications of MC2LP problems. This volume integrates their main research results ranging from theoretical bases to broad areas of real world applications. The theoretical bases include the formulation of MC2LP; integer MC2LP and MC2 transportation model; fuzzy MC2LP and fuzzy duality of MC2LP; optimal system designs and contingency plans; MC2 decision support system; and MC2 computer software development. The application areas are accounting, management information systems, production planning, and telecommunications management.The book serves as a seminar text for both undergraduates and graduates who have a linear algebra or equivalent background. For practitioners, it will help in handling LP type problems in multiple decision making environment.

Presents an overview of the main issues of data mining, including its classification, regression, clustering, and ethical issues. Provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications.

With the advent of powerful computers and novel mathematical programming techniques, the multidisciplinary field of optimization has advanced to the stage that quite complicated systems can be addressed. The conference was organized to provide a platform for the exchange of new ideas and information and for identifying needs for future research. The contributions covered both theoretical techniques and a rich variety of case studies to which optimization can be usefully applied.

This volume constitutes the proceedings of the Fifth International Conference on Multi-Objective Programming and Goal Programming: Theory & Appli cations (MOPGP'02) held in Nara, Japan on June 4-7, 2002. Eighty-two people from 16 countries attended the conference and 78 papers (including 9 plenary talks) were presented. MOPGP is an international conference within which researchers and prac titioners can meet and learn from each other about the recent development in multi-objective programming and goal programming. The participants are from different disciplines such as Optimization, Operations Research, Math ematical Programming and Multi-Criteria Decision Aid, whose common in terest is in multi-objective analysis. The first MOPGP Conference was held at Portsmouth, United Kingdom, in 1994. The subsequent conferenes were held at Torremolinos, Spain in 1996, at Quebec City, Canada in 1998, and at Katowice, Poland in 2000. The fifth conference was held at Nara, which was the capital of Japan for more than seventy years in the eighth century. During this Nara period the basis of Japanese society, or culture established itself. Nara is a beautiful place and has a number of historic monuments in the World Heritage List. The members of the International Committee of MOPGP'02 were Dylan Jones, Pekka Korhonen, Carlos Romero, Ralph Steuer and Mehrdad Tamiz.

In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.

criteria linear and nonlinear programming has proven to be a very useful approach. • Knowledge management for enterprise: These papers address various issues related to the application of knowledge management in corporations using various techniques. A particular emphasis here is on coordination and cooperation. • Risk management: Better knowledge management also requires more advanced techniques for risk management, to identify, control, and minimize the impact of uncertain events, as shown in these papers, using fuzzy set theory and other approaches for better risk management. • Integration of data mining and knowledge management: As indicated earlier, the integration of these two research fields is still in the early stage. Nevertheless, as shown in the papers selected in this volume, researchers have endearored to integrate data mining methods such as neural networks with various aspects related to knowledge management, such as decision support systems and expert systems, for better knowledge management. September 2004 Yong Shi Weixuan Xu Zhengxin Chen CASDMKM 2004 Organization Hosted by Institute of Policy and Management at the Chinese Academy of Sciences Graduate School of the Chinese Academy of Sciences International Journal of Information Technology and Decision Making Sponsored by Chinese Academy of Sciences National Natural Science Foundation of China University of Nebraska at Omaha, USA Conference Chairs Weixuan Xu, Chinese Academy of Sciences, China Yong Shi, University of Nebraska at Omaha, USA Advisory Committee

The volume provides users and developers of the IT/S (information technology and systems) with information about the advances in decision making and decision-making support that empower and enable information technology in the direction of productivity and effectiveness of decision making in business. The chapters have been written by well-known international experts in decision making and they explore the frontiers of decision making in the era of IT/S.The book is intended to serve as a research source, scientific reference and business support source, as well as a book of student readings that will appeal to a larger international audience.

This textbook presents methodologies and applications associated with multiple criteria decision analysis (MCDA), especially for those students with an interest in industrial engineering. With respect to methodology, the book covers (1) problem structuring methods; (2) methods for ranking multi-dimensional deterministic outcomes including multiattribute value theory, the analytic hierarchy process, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and outranking techniques; (3) goal programming,; (4) methods for describing preference structures over single and multi-dimensional probabilistic outcomes (e.g., utility functions); (5) decision trees and influence diagrams; (6) methods for determining input probability distributions for decision trees, influence diagrams, and general simulation models; and (7) the use of simulation modeling for decision analysis. This textbook also offers: · Easy to follow descriptions of how to apply a wide variety of MCDA techniques · Specific examples involving multiple objectives and/or uncertainty/risk of interest to industrial engineers · A section on outranking techniques ; this group of techniques, which is popular in Europe, is very rarely mentioned as a methodology for MCDA in the United States · A chapter on simulation as a useful tool for MCDA, including ranking & selection procedures. Such material is rarely covered in courses in decision analysis · Both material review questions and problems at the end of each chapter . Solutions to the exercises are found in the Solutions Manual which will be provided along with PowerPoint slides for each chapter. The methodologies are demonstrated through the use of applications of interest to industrial engineers, including those involving product mix optimization, supplier selection, distribution center location and transportation planning, resource allocation and scheduling of a medical clinic, staffing of a call center, quality control, project management, production and inventory control,and so on. Specifically, industrial engineering problems are structured as classical problems in multiple criteria decision analysis, and the relevant methodologies are demonstrated.

This book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theory of Data Science, Data Science of People and Health, Web of Data, Data Science of Trust and Internet of Things.

The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.