Quantitative models for optimal rest period scheduling

Gentzler, G.L.; Khalil, Magdy T.; Sivazlian, B.D.

doi:10.1016/0305-0483(77)90104-9

Cited by 21 publications

(7 citation statements)

References 10 publications

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“…The simulation model was used to numerically perform sensitivity analysis. In a short note, Bechtold (1979) complements the numerical sensitivity analysis approach of Gentzler et al (1977) with an analytic sensitivity analysis approach.…”

Section: Operations Research Approaches To Work-rest Schedulingmentioning

confidence: 98%

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Taxonomy for integrating scheduling theory and human factors: Review and research opportunities

Lodree

Geiger

Jiang

2009

International Journal of Industrial Ergonomics

102

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Section: Operations Research Approaches To Work-rest Schedulingmentioning

confidence: 98%

“…A linear rate of recovery was assumed. Gentzler et al (1977) modeled multiple breaks using a mathematical model as well as a simulation model. The length of each break was fixed and always ensured full recovery, and the work rate declined at a linear or exponential rate.…”

Section: Operations Research Approaches To Work-rest Schedulingmentioning

confidence: 99%

Taxonomy for integrating scheduling theory and human factors: Review and research opportunities

Lodree

Geiger

Jiang

2009

International Journal of Industrial Ergonomics

102

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“…Scheduling a Rest Period for a Work Group, 4 Eilon (1964) pioneered the concept of modeling performance with the objective of determining the optimal length and placement of one rest period, over a finite time horizon, for a single employee. Gentzler, Khalil and Sivazlian (1977) and Bechtold (1979) developed multirest period models for individuals over infinite and finite time horizons, respectively.…”

Section: Scheduling a Rest Period For Amentioning

confidence: 99%

Optimal Scheduling of a Flexible-Duration Rest Period for a Work Group

Bechtold

Thompson

1993

Operations Research

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All previous modeling research involving optimization of performance associated with work-rest cycles has focused upon individual employees working independently. We extend this earlier research by considering the choices of placement for and duration of a single rest period that must be taken simultaneously by all employees in a work group. Assuming linear work-rate decay and recovery functions for individual employees within the group, we show that an appropriate model can be formulated as a mixed-binary, cubic programming problem. We develop an efficient optimal solution procedure with a computational time that appears to be a linear function of the number of employees considered. We report on a preliminary simulation experiment that evaluates the productivity loss that occurs when the rest break policy is determined based on the work characteristics of a randomly selected subset of employees in the work group, and provides an initial exploration of the nature of optimal policy variables. Finally, we offer suggestions for future research.

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“…In the selective maintenance studies mentioned above, the work rate decay of a repairperson is ignored and the duration of the maintenance action is usually assumed to be determined or follow a certain distribution 15,23 . However, in practice, the work rate of a repairperson will decay due to the fatigue effect 8,30,31 . For example, a repairperson needs to hold the wrench and install the screws when repairing car chassis components.…”

Section: Introductionmentioning

confidence: 99%

Selective maintenance of multi‐state systems with the repairperson fatigue effect and stochastic break duration

Liu

Xiao

Yang

et al. 2022

Quality & Reliability Eng

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Systems in the industry are often required to execute a sequence of missions, and the state of the multi‐state systems may deteriorate with the increasing of running time. To improve the system reliability of the next mission, selective maintenance is applied in the limited break. Due to the fatigue effect, the work rate of the repairperson decays with time. However, the existing selective maintenance studies do not consider the impact of fatigue effect on work rate, which leads to underestimating the duration of maintenance actions and overestimating the system reliability. To overcome the above problems, a new selective maintenance model for multi‐state systems is developed to maximize the system reliability of the next mission. First, the decay process of the work rate of a repairperson is described as a piecewise continuous decreasing exponential function of working time. Next, a homogenous discrete‐state continuous‐time Markov process is used to describe the performance capacity degradation of components. Considering the stochastic break duration, based on the state probability distribution of each component obtained by the Markov model, the universal generation function (UGF) method is applied to evaluate the multi‐state system reliability. Then, taking the selected maintenance actions and maintenance priority as decision variables, the resulting selective maintenance optimization problem is solved by a tailored genetic algorithm. Finally, two computational experiments are carried out to demonstrate the effectiveness of the proposed method.

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Quantitative models for optimal rest period scheduling

Cited by 21 publications

References 10 publications

Taxonomy for integrating scheduling theory and human factors: Review and research opportunities

Taxonomy for integrating scheduling theory and human factors: Review and research opportunities

Optimal Scheduling of a Flexible-Duration Rest Period for a Work Group

Selective maintenance of multi‐state systems with the repairperson fatigue effect and stochastic break duration

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