Healthcare Staff Scheduling

Michael Mutingi is a lecturer in industrial engineering in the Faculty of Engineering and Technology at the University of Botswana. He has professional experience as a research associate at the National University of Singapore and as a lecturer in industrial engineering at the National University of Science & Technology, Zimbabwe. He is completing his PhD in engineering management at the University of Johannesburg, South Africa, majoring in healthcare operations management. Mutingi obtained his MEng and BEng in industrial engineering from the National University of Science & Technology, Zimbabwe. He researches healthcare operations management, supply chain management, manufacturing systems, biologically inspired metaheuristic optimization, and operations research applications. Michael Mutingi is a member of the Southern African Institution of Industrial Engineers and the System Dynamics Society. He has published in international journals, such as Computers & Industrial Engineering, Production Planning & Control, Journal of Intelligent Manufacturing, International Journal of Production Research, and Maintenance & Reliability. Charles Mbohwa is a professor of operations management at the University of Johannesburg, South Africa. Previously he was a senior lecturer in Mechanical Engineering at the University of Zimbabwe and a mechanical engineer at the National Railways of Zimbabwe. He has a doctor of engineering from the Tokyo Metropolitan Institute of Technology, an MSc in operations management and manufacturing systems from the University of Nottingham, UK, and a BSc with honors in mechanical engineering from the University of Zimbabwe. He has been a British Council Scholar, a Japan Foundation Fellow, a Heiwa Nakajima Fellow, a Kubota Foundation Fellow, and a Fulbright Fellow. His research interests are in operations management, engineering management, supply chain managem

"This book has applied emerging optimization approaches, such as the simulated metamorphosis algorithm and the fuzzy grouping genetic algorithm, for solving homecare personnel scheduling problems which are very complex. The book will be an asset to the homecare sector for solving their scheduling problems." -Professor Godfrey Onwubolu, Sheridan Institute of Technology & Advanced Learning, Brampton, Canada "The book provides a definitive guide on fuzzy metaheuristic approaches, which is a welcome development for researchers in the area. Biologically inspired metaheuristics have been proven to offer some of the best solution methods to solving hard combinatorial problems. This book extends the utility of the approaches by combining them with fuzzy theory concepts, which allows them to more efficiently handle problems characterized by imprecision, fuzziness and vagueness." -Dr Herbert Mapfaira, University of Botswana

• Introduction. Emerging Fuzzy Optimization Approaches. Research Applications. Appendix: Fuzzy Set Theory Concepts.