Models and Methods for Interval-Valued Cooperative Games in Economic Management, 1st ed. 2016

This book proposes several commonly used interval-valued solution concepts of interval-valued cooperative games with transferable utility. It thoroughly investigates these solutions, thereby establishing the properties, models, methods, and applications. The first chapter proposes the interval-valued least square solutions and quadratic programming models, methods, and properties. Next, the satisfactory-degree-based non-linear programming models for computing interval-valued cores and corresponding bisection algorithm are explained.  Finally, the book explores several simplification methods of interval-valued solutions:  the interval-valued equal division and equal surplus division values; the interval-valued Shapley, egalitarian Shapley, and discounted Shapley values; the interval-valued solidarity and generalized solidarity values; and the interval-valued Banzhaf value.

This book is designed for individuals from different fields and disciplines, such as decision science, game theory, management science, operations research, fuzzy sets or fuzzy mathematics, applied mathematics, industrial engineering, finance, applied economics, expert system, and social economy as well as artificial intelligence. Moreover, it is suitable for teachers, postgraduates, and researchers from different disciplines: decision analysis, management, operations research, fuzzy mathematics, fuzzy system analysis, applied mathematics, systems engineering, project management, supply chain management, industrial engineering, applied economics, and hydrology and water resources.

Establishes a series of formulas, methods and properties of commonly used interval-valued solutions of interval-valued cooperative games

Presents improvements to modern interval-valued game theory and methods, including new linear programming models that surpass traditional and fuzzy optimizations

Proposes innovative game methods for interactive management problems with interval-valued data

Designed for readers across various disciplines

Includes supplementary material: sn.pub/extras