Michael Mutingi – författare

Healthcare operations, in hospitals and home healthcare settings, are inundated with complex fuzzy features that impose difficulties in the creation of work schedules. This book presents in-depth research on emerging approaches to healthcare staff scheduling. It starts by reviewing the key issues and challenges inherent in staff scheduling, along with the basic concepts of fuzzy set theory. Examining cutting-edge research applications, it details fuzzy optimization algorithms derived from biologically inspired approaches and fuzzy theory. Facilitating a practical and in-depth understanding of modern fuzzy metaheuristic optimization approaches, the book presents recent research on multi-criteria algorithms and their applications in healthcare operations, particularly staff scheduling.

Digital Business Transformation in Healthcare: Advances, Models, Strategies and Frameworks provides a comprehensive view of digital transformation, outlining challenges and barriers while also emphasizing critical success factors for healthcare digital transformation. The book introduces healthcare readiness and maturity models, enabling healthcare systems to choose appropriate roadmaps for digital transformation. By utilizing these models, healthcare providers can select effective and sustainable strategies for their digital transformation journey, avoiding the negative impacts of fragmented technology adoption.It is designed for both professionals already immersed in the healthcare industry and those seeking advanced knowledge in digital business transformation within healthcare.Assesses the key aspects, nature, and dimensions of digital transformation from the healthcare service perspectiveOffers readiness and maturity data models specific to the healthcare service industryPresents the inherent challenges and barriers associated with the adoption of emerging healthcare technologies

This book presents hybrid value stream mapping tools for developing Lean and green supply chains. The tools incorporate green and Lean concepts that can assist supply chain decision makers to simultaneously minimize wastes, costs, environmental damage, and energy and material usage In addition, it provides a new integrated approach for evaluating supply chain performance from both green and Lean perspectives. As supply chain stakeholders increasingly become aware of the need to simultaneously address economic, environmental, and energy usage issues, it is essential to formulate performance objectives based on these issues. To achieve these objectives, the book provides tools and techniques for value stream mapping the supply chain. Suggested tools, such as green lean process mapping, quality filter mapping, energy value stream mapping, and supply chain response matrix can assist supply chain decision makers to simultaneously achieve green and Lean objectives centered on minimizing wastes, costs, environmental damage, as well as energy and material usage. The book is divided into three parts. Part I presents recent concepts of green and Lean paradigms, as well as green Lean performance in supply chain systems. Part II presents parallel and integrated green Lean models, based on the triple bottom line (also known as the 3E bottom line) perspective, covering aspects related to the economy, the environment, and energy and material usage. Part III presents and explains a range of tools and techniques, where Leanness and greenness are emphasized from a common view point. A compendium of Lean green value stream mapping tools are presented and illustrated using succinct procedures, flowcharts and examples.

Healthcare operations, in hospitals and home healthcare settings, are inundated with complex fuzzy features that impose difficulties in the creation of work schedules. This book presents in-depth research on emerging approaches to healthcare staff scheduling. It starts by reviewing the key issues and challenges inherent in staff scheduling, along with the basic concepts of fuzzy set theory. Examining cutting-edge research applications, it details fuzzy optimization algorithms derived from biologically inspired approaches and fuzzy theory. Facilitating a practical and in-depth understanding of modern fuzzy metaheuristic optimization approaches, the book presents recent research on multi-criteria algorithms and their applications in healthcare operations, particularly staff scheduling.

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms.Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.