Robert Fuller – författare

Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing the Bullwhip Effect", summarizes research work focused on the demand fluctuations in supply chains. The program enhanced existing theoretical frameworks with fuzzy logic modeling. Chapter 6, "Knowledge Management", outlines the collection, storing, transfer and management of knowledge using fuzzy logic. The principles are worked out in detail with software agents. Chapter 7, "Mobile Technology Application", introduces various applications including empirical facts and how mobile technology can be supported with software agents.

Implicitly the book develops themes that successful companies should use to (1) master effectiveness and quality in both the details and the whole, (2) build on and work with flexibility, and (3) support continuous learning in both the organizational and the individual level.

This book constitutes the post-conference proceedings of the 12th International Workshop on Fuzzy Logic and Applications, WILF 2018, held in Genoa, Italy, in September 2018.

Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control.

The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design.

The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule interpolation, subjective weights based meta learning in multi criteria decision making, swarm-based heuristics for an area exploration and knowledge driven adaptive product representations.

The last part addresses different problems, issues and methods of applied mathematics. This includes perturbation estimates for invariant subspaces of Hessenberg matrices, uncertainty and nonlinearity modelling by probabilistic metric spaces and comparison and visualization of the DNA of six primates.

This book starts with the basic concepts of fuzzy sets and progresses through a normative view on possibility distributions and OWA operators in multiple criteria decisions.  

Five applications  (that all build on experience from solving complex real world problems) of possibility distributions to strategic decisions about closing/not closing a production plant using fuzzy real options,  portfolio selection with imprecise future data, predictive probabilities and possibilities for risk assessment in grid computing, fuzzy ontologies for process industry, and  design (and implementation) of mobile value services are presented and carefully discussed. It can be useful for researchers and students working in soft computing, real options, fuzzy decision making, grid computing, knowledge mobilization and mobile value services.