A dissimilarities balance model for a multi-skilled multi-location food safety inspector scheduling problem

ABSTRACT

In this work, we examine a staff scheduling problem in a governmental food safety center that is responsible for the surveillance of imported food at an international airport. In addition to the fact that the staff have different levels of efficiency and have different preference for work shifts, the Operations Manager of the food safety center would like to balance the dissimilarities of workers in order to provide unbiased work schedules for staff members. We adopt a two-phase approach, where the first phase is to schedule the work shifts of food safety inspectors (including rest days and shift types) with schedule fairness and staff preference taken into account and the second phase is to best-fit them to tasks in terms of skill-matches and create diversity of team formations. We also provide polyhedral results and devise valid inequalities for the two formulations. For the first-phase problem, we relax some constraints of the fairness criteria to reduce the problem size to reduce computational effort. We derive an upper bound for the objective value of the relaxation and provide computational results to show that the solutions devised from our proposed methodology are of good quality. For the second-phase problem, we develop a shift-by-shift assignment heuristic to obtain an upper bound for the maximum number of times any pair of workers is assigned to the same shift at the same location. We propose an enumeration algorithm, that solves the problems for fixed values of this number until an optimality condition holds or the problem is infeasible. Computational results show that our proposed approach can produce solutions of good quality in a much shorter period of time, compared with a standalone commercial solver.

Keywords:

• Workforce scheduling
• schedule fairness
• team composition
• skill competency
• staff preferences

Acknowledgements

The authors are grateful to the Operations Manager of the food safety center for providing information on the basic background of their daily operations and first-hand knowledge of the constraints associated with scheduling staff members. We are also indebted to the Editors and the anonymous referees for their valuable comments and suggestions.

Funding

The research of the first author is partially supported by a grant from the Asian Institute of Supply Chains and Logistics (project no. 8116027) and a grant from PROCORE: France/Hong Kong Joint Research Scheme of Research Grant Council Hong Kong and the Consulate General of France in Hong Kong (project no. 2900239). The research of the second author is supported by Microsoft Research Asia Collaborative Research Fund (grant no. FY15-RES-THEME-049) and Macao Science and Technology Development Fund (grant no. 088/2013/A3).

Additional information

Notes on contributors

Chun-Hung Cheng

Chun-Hung Cheng obtained his Ph.D. from the University of Iowa. While he was a graduate student, he worked at the University of Iowa Hospital & Clinics as a programming analyst. He started his teaching career at Kentucky State University. Later, he returned to Hong Kong. His research reflects his interest in information systems and operations management. His work has been published in internationally reputed journals, including the ACM Transactions on Information Systems, Annals of Operations Research, Computers & Operations Research, European Journal of Operational Research, Expert Systems, IEEE Transactions on Engineering Management, IEEE Transactions on Systems, Man, and Cybernetics, IIE Transactions, Information and Management, Journal of Information Technology, Journal of Supply Chain Management, Omega, Operations Research, etc. His earlier work (together with Professor W.J. Boe) on factory layout was implemented by a third-party developer for a toy manufacturer in South Brazil. He has recently led a project team to design and implement operational systems for an air-mail center and two museums in Hong Kong. He has also provided consulting services to local industries.

Yong-Hong Kuo

Yong-Hong Kuo is a Research Assistant Professor in the Stanley Ho Big Data Decision Analytics Research Centre at the Chinese University of Hong Kong. He earned his B.Sc. in Mathematics with a minor in Risk Management Science and M.Phil. and Ph.D. in Systems Engineering and Engineering Management, all from the Chinese University of Hong Kong. During his studies, he worked at the University of California at Berkeley as a Visiting Researcher and Oak Ridge National Laboratory as a Research Student. Prior to returning to the Chinese University of Hong Kong, he was an Assistant Professor at the School of Business at Macau University of Science and Technology. His research interests include operations research, combinatorial optimization, logistics management, system simulation, and healthcare management. His publications have appeared in internationally reputed journals including IIE Transactions and Production and Operations Management.