Production scheduling is an important function that determines the efficiency and productivity of a production system. Many optimization methods, techniques, tools, and heuristics have been used to solve production scheduling problems, accordingly priority rules are implemented for customers' orders in real-world applications. Simulations and heuristic methods are quite useful for making decisions, and they are used mostly to design and improve production systems by reducing their complexity. In this study, a Priority Rule-Based Genetic Algorithm Scheduling (PRGA-Sched) module was developed to provide shorter total completion time in production scheduling. The module was integrated with the Faborg-Sim simulation tool. As a case study, a heating boiler manufacturing system was analyzed and simulated with six products and customers' orders by using production data from the PRGA-Sched module in Faborg-Sim. The results showed that a shorter total completion time is obtained and saved than the initial situation by via PRGA-Sched module.

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Burnout rates and dissatisfaction among healthcare workers remain high due to long working hours. One possible solution to this problem is to let them choose their weekly working hours and starting times in order to achieve a work-life balance. Moreover, a scheduling process that responds to changing healthcare demands at different times of the day should increase work efficiency in hospitals. In this study, a methodology and software were developed to schedule hospital personnel, taking into account their preferences regarding working hours and starting time. The software also allows the hospital management to determine the number of staff needed at different times of the day. Three methods and five working-time scenarios characterized by different divisions of working time are proposed to solve the scheduling problem. The Seniority score Priority assignment Method appoints personnel prioritizing seniority, whereas the newly developed Balanced and Fair assignment Method and Genetic Algorithm Method aim for a more nuanced distribution. The methods proposed were applied to physicians in the internal diseases department in a specific hospital. Weekly/monthly scheduling of all employees was carried out with the software. The results of scheduling factoring in work-life balance, and the performances of algorithms are shown for the hospital where the application was trialled.