Abstract This research aims to incorporate human factors engineering into the scheduling theory in order to exploit optimized human performance. Staff scheduling issue in which part-time employees have variable performance was studied in this paper. Objective function of the mathematical model is to minimize staffing costs and provided model tries to determine best shifts duration and employees assignments. The unique characteristic and novelty of this study is consideration of ergonomic aspect (fatigue rate of employees) in staff scheduling problem. We used genetic algorithm to solve model. In order to examine effectiveness and efficiency of the model, a set of problems were solved. Also efficiency of GA algorithm results were compared against LINGO results. Comparison of results demonstrated that GA algorithm has good ability to find satisfying solution in reasonable computational running time. This study showed that we can model human fatigue in employee scheduling and planning and consider flexible working shifts to decrease labor cost and increase production efficiency. In order to study policies of decreasing labor fatigue and increasing his/her working capacity, applying provided model were suggested for comparing cost of policies (such as education, job rotation, automation and …) against economic benefits of them in scheduling and choosing the best.

Abstract The goal of this research is providing optimization approach for bi-objective scheduling work shifts and job rotation problem in order to exploit efficient performance of employees. In this article scheduling work shifts and job rotation problems had been modeled in one mathematical model with two objective functions: minimizing labor cost and maximizing number of job rotation. Also human factors (fatigue, learning and forgetting) that have effect on workers performance were modeled. Presented model was mixed integer and nonlinear and genetic algorithm and ε-constraint technique have been used to solve it and gain Pareto sets. To illustrate efficiency of provided algorithm, its performance has been compared to results of LINGO. The results indicated that performance of genetic algorithm is better than that of LINGO in terms of computational time and objective value. To relate relationship between objectives, set of problems have been solved. Obtained Pareto indicated that there is a conflict between objectives. Hence with considering human factors that have effect on workforce’s performance it is needed to plan work shifts and job rotation simultaneously. Results indicated that the proposed optimization approach is capable to provide suitable alternatives while managers try to consider decreasing cost, increasing jobs variety and multi-skilled training.

Abstract Psychological capital is a new concept that has been discussed in the third millennium and entered in the field of management since 2006 Due to its unique role in organizational wealth-generation, it has become in the core attention of scholars and intellectuals research in the field of behavior, human resource management and human capital. So the main goal of this paper is designing a model to improve psychological capital in Iranianpublic organizations with identifying the role of human resource functions. This research has employed quantitative approach and followed correlation method. The populations for this study were employees of public organizations; the rational for selection of them was classification system in the governmental budget. Accordingly, they were classified into the three categories of general, social and economic. On the other hand, due to the wide dispersion and large organizations across the country, public organizations of Tehran province were chosen as key clusters. The research method is descriptive correlation study, and the data were collected using standard questionnaires. The data were analyzed by using structural equations and multiple regressions. The research findings showed that HR functions have significant positive relation with the psychological capital; however when organizational justice is placed as the intervening variable between them, the correlation coefficient is increased. The results also indicated that HRM functions have the greatest effect on Psycap by organizational justice. At last, fitness test of the model demonstrated that it is suitable for Iranian public organizations.