Investigating the impacts of human factors of learning, forgetfulness and fatigue and refreshment on staff scheduling

Behnaz Khadem


The present study has investigated the impacts of human factors of learning, forgetfulness and fatigue and refreshment on staff scheduling. It aims to present a mathematical model for staff scheduling so that workforce costs are minimized and the factors of learning, forgetfulness and fatigue of employees, which affect their performance and enhance their efficiency, are taken into account. Parameters of the proposed model comprise the fixed and variable costs of worker assignment, the individual’s production rate at different times of work shift, the forgetfulness parameter (which indicates the degree to which a person forgets the skill in performing a task), the learning rate, the amount of time away from work and so on. The variables of the proposed model also indicate worker assignment to the work shifts. After validating the proposed model, several problems have been generated in different dimensions and have been solved by GAMS software. Further, to solve high-dimensional problems, a genetic algorithm was developed, by which the problem was solved in various dimensions. The algorithm accuracy was examined by comparing its results with the exact solution results and its problem-solving ability was also evaluated using the generation of problems in various dimensions and their solutions.


Human factors, learning, forgetfulness, fatigue, staff scheduling

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Akbari, M. (2017a). Mathematical modeling of human factors in a dual constraint system. New Research in Decision-Making, 2(2), 23-49, Article 2.

Akbari, M. (2017a). Temporary staff scheduling with variable productivity. Management Research in Iran, 21(3), 25-47, Article 2.

Akbari, M., Dori, B. & Zandiyeh, M. (2012). Multi-skilled staff work shift scheduling with a genetic algorithm approach. Industrial Management Perspective, 2(7).

Dori, B., Akbari, M. & Zandiyeh, M. (2013). Dual objective scheduling of work shifts and job rotation of multi-skilled staff with a human factor engineering approach. Management Research in Iran, 17(3), 1-21.

Cai, X. and Li, K.N., (2000). A genetic algorithm for scheduling staff of mixed skills under ‎multi-criteria. European Journal of Operational Research, 125(2), 359-369.‎‏ ‏

Ernst, A.T., Jiang, H., M. Krishnamoorthy, B. Owens and D. Sier, An Annotated ‎Bibliography of Personnel Scheduling and Rostering. Annals of Operations Research 2004. ‎‎127: p. 21-144.‎

Ernst, A.T., H. Jiang, M. Krishnamoorthy, D. Sier, Staff scheduling and rostering: A review ‎of applications, methods and models. European Journal of Operational Research, 2004. 153: ‎p. 3-27‎

Guastello, S.J., (2006) Human factors engineering and ergonomics: a systems‏ ‏approach: ‎Lawrence Erlbaum Associates.‎

Ahuja, H., R. Sheppard, Computerized Nurse Scheduling. Industrial Engineering, 1975. ‎‎7(10): p. 24-29.‎

Hesham, K.A., Survey, Categorization, and Comparison of Recent Scheduling Literature. ‎Annals of Operations Research 2004. 127: p. 145-175.‎

Nembhard, D.A. and Uzumeri, M.V. (2000). An Individual-Based Description of‏ ‏Learning ‎within an Organization. IEEE Transactions on Engineering ‎

Othman M., Gouw G. J., Bhuiyan N. (2012) "Workforce scheduling: A new‏ ‏model ‎incorporating human factors"; Journal of Industrial Engineering and‏ ‏Management, 5(2): 259-‎‎284‎‏.‏

Topaloglu, S., Ozkarahan, I. , An Implicit Goal Programming Model for the Tour ‎Scheduling Problem Considering the Employee Work Preferences Annals of Operations ‎Research, 2004. 128: p. 135-158.‎


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