Wonderful Solutions and Habitual Domains for Challenging Problems in Changeable Spaces
From Theoretical Framework to Applications

Authors: Moussa Larbani, Po-Lung Yu



Introduces a new decision theory, Optimization in Changeable Spaces

Illustrates how to expand competences, handle environmental, psychological and behavioral aspects and their dynamics when solving challenging decision problems

Includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction

Relevant to academics, managers and policy makers

This book introduces a new paradigm called ‘Optimization in Changeable Spaces’ (OCS) as a useful tool for decision making and problem solving. It illustrates how OCS incorporates, searches, and constructively restructures the parameters, tangible and intangible, involved in the process of decision making. The book elaborates on OCS problems that can be modeled and solved effectively by using the concepts of competence set analysis, Habitual Domain (HD) and the mental operators called the 7-8-9 principles of deep knowledge of HD. In addition, new concepts of covering and discovering processes are proposed and formulated as mathematical tools to solve OCS problems. The book also includes reformulations of a number of illustrative real-life challenging problems that cannot be solved by traditional optimization techniques into OCS problems, and details how they can be addressed. Beyond that, it also includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction. This book will be of interest to managers of businesses and institutions, policy makers, and educators and students of decision making and behavior in DBA and/or MBA.

Table of contents

Front Matter

Challenging Decision Problems and Decision Models

Decision Processes and Decision-Making in Changeable Spaces

Habitual Domains, Human Behaviour Mechanism and Wonderful Solutions for DMCS Problem Analysis

Expansion of Habitual Domains and DMCS

Competence Set Analysis, Decision Blinds and Decision-Making

Decision-Making in Changeable Spaces (DMCS): A New Paradigm

Solving Real-World DMCS Problems, Part 1: Management and Economics Problems

Solving Real-World DMCS Problems, Part 2: Social, Geopolitical, and Discovery Problems

Innovation Dynamics as a DMCS Problem

Conclusion and Further Research

Back Matter