A satisficing approach to home healthcare worker scheduling
- Mutingi, Michael, Mbohwa, Charles
- Authors: Mutingi, Michael , Mbohwa, Charles
- Date: 2013
- Subjects: Home healthcare staff scheduling , Fuzzy sets
- Type: Article
- Identifier: uj:6174 , ISBN 978-93-82242-26-0 , http://hdl.handle.net/10210/13781
- Description: The homecare worker scheduling problem is inundated with fuzzy and often conflicting goals, constraints and preferences. In such an uncertain environment, the decision maker needs to find a satisficing solution approach that takes into account the humanistic judgments and the conflicting nature of the goals. This paper proposes a fuzzy satisficing approach, based on fuzzy set theory, for addressing the homecare worker scheduling problem. The aim is to provide a satisficing approach that considers the management goals, the worker preferences, as well as the service quality as specified by the healthcare clients. By addressing the desired goals or preferences of the three players, (i) the management, (ii) the worker, and (iii) the client, the approach provides a more realistic, flexible and adaptable method for real-world healthcare staff scheduling in an uncertain environment.
- Full Text:
- Authors: Mutingi, Michael , Mbohwa, Charles
- Date: 2013
- Subjects: Home healthcare staff scheduling , Fuzzy sets
- Type: Article
- Identifier: uj:6174 , ISBN 978-93-82242-26-0 , http://hdl.handle.net/10210/13781
- Description: The homecare worker scheduling problem is inundated with fuzzy and often conflicting goals, constraints and preferences. In such an uncertain environment, the decision maker needs to find a satisficing solution approach that takes into account the humanistic judgments and the conflicting nature of the goals. This paper proposes a fuzzy satisficing approach, based on fuzzy set theory, for addressing the homecare worker scheduling problem. The aim is to provide a satisficing approach that considers the management goals, the worker preferences, as well as the service quality as specified by the healthcare clients. By addressing the desired goals or preferences of the three players, (i) the management, (ii) the worker, and (iii) the client, the approach provides a more realistic, flexible and adaptable method for real-world healthcare staff scheduling in an uncertain environment.
- Full Text:
A fuzzy genetic algorithm for healthcare staff scheduling
- Mutingi, Michael, Mbohwa, Charles
- Authors: Mutingi, Michael , Mbohwa, Charles
- Date: 2013
- Subjects: Healthcare staff scheduling , Fuzzy-based genetic algorithm , Fuzzy sets
- Type: Article
- Identifier: uj:6172 , ISBN 978-93-82242-26-0 , http://hdl.handle.net/10210/13779
- Description: In the presence of multiple conflicting objectives and constraints, healthcare staff scheduling is complex. This research presents a fuzzy-based genetic algorithm (FGA) for handling multiple conflicting objectives and constraints common in healthcare manpower scheduling problems. Fuzzy set theory is used for genetic evaluations of alternative staff schedules by representing the fitness of each alternative solution as a fuzzy membership functions. The proposed FGA framework is designed to incorporate the often imprecise decision maker’s preferences and choices in terms of weights. The framework is also designed to provide a population of alternative solutions for the decision maker, rather than prescribe a single decision. It is anticipated that the FGA procedure forms a useful decision support tool for healthcare staff scheduling in a fuzzy environment with multiple conflicting objectives and constraints.
- Full Text:
- Authors: Mutingi, Michael , Mbohwa, Charles
- Date: 2013
- Subjects: Healthcare staff scheduling , Fuzzy-based genetic algorithm , Fuzzy sets
- Type: Article
- Identifier: uj:6172 , ISBN 978-93-82242-26-0 , http://hdl.handle.net/10210/13779
- Description: In the presence of multiple conflicting objectives and constraints, healthcare staff scheduling is complex. This research presents a fuzzy-based genetic algorithm (FGA) for handling multiple conflicting objectives and constraints common in healthcare manpower scheduling problems. Fuzzy set theory is used for genetic evaluations of alternative staff schedules by representing the fitness of each alternative solution as a fuzzy membership functions. The proposed FGA framework is designed to incorporate the often imprecise decision maker’s preferences and choices in terms of weights. The framework is also designed to provide a population of alternative solutions for the decision maker, rather than prescribe a single decision. It is anticipated that the FGA procedure forms a useful decision support tool for healthcare staff scheduling in a fuzzy environment with multiple conflicting objectives and constraints.
- Full Text:
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