Bøger af Michael Mutingi

Healthcare operations, in hospitals and home healthcare settings, are inundated with complex fuzzy features that impose difficulties in the creation of work schedules. As healthcare workers call for schedules that accommodate their individual preferences and patients continue to call for more personalized healthcare, further research into multi-criteria solution approaches to staff scheduling is imperative.Healthcare Staff Scheduling: Emerging Fuzzy Optimization Approaches presents in-depth research into 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 research applications in healthcare staff scheduling, it details promising fuzzy optimization algorithms derived from biologically inspired approaches and fuzzy theory.Providing researchers, operations analysts, scientists, and practitioners with a practical and in-depth understanding of modern fuzzy metaheuristic optimization approaches, the book presents cutting-edge research on multi-criteria algorithms and their applications in healthcare operations, particularly in staff scheduling.The book illustrates flexible techniques for solving complex scheduling problems that account for the variability that results from imprecise human preferences. Covering recent developments in the methods utilized to create high-quality staff schedules, it includes many instructive examples of healthcare schedule problems along with potential solutions.Considering avenues for future research, this book will help readers pave the way to new and improved methods for solving staff scheduling problems that are difficult to evaluate quantitatively due to imprecision, fuzziness, and vagueness.To promote the quality of the work presented, all chapters in this book have been rigorously reviewed by leading international experts and researche

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment.