The workforce staffing and scheduling Problems Based on Annualized Hours

• Main Authors: Tsaur Jia Haur, 曹家豪
• Other Authors: Huang Rong Hwa
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/96446601194520127850

碩士 === 輔仁大學 === 管理學研究所 === 90 === The workforce staffing and scheduling policy under the contract based on annualized hours meet seasonal fluctuating demand. This method is a new and practical idea. A lot of European and American firms have successfully used annualized hours. Annualized Hours harness contracted method with employees for one year or a period of time. The way of calculating the payment is based on how many hours an employee works for contracted period. Employers can require employees to work more when a firm is busy. If a firm has less work they can decline employees’ working hours. Only when an employee’s working period exceeds the contracted hours, an employer would give them the overtime payment. Annualized Hours provide employers and employees a flexible working style. As long as an employer has flexible human resources, employees would have more time to have their vacation. There is seldom staffing and scheduling research under Annualized Hours. This paper discusses the AH method in the three parts. The first part presents staffing decision, and develops an algorithm. The algorithm is to improve the present algorithm and fit the company’s need. Then, we use the example to state it. Secondly, we build up performance appraisal criteria to evaluate the scheduling operations which improvement under our algorithm. In the third part, we use Integer Programming to carry out the scheduling operations. We divided this part into two kinds of condition. First, we discuss the company’s working day less than seven days. On this situation, there wouldn’t appear over sequential working days. Second we discuss the company working seven days. We can consider this situation as a full year wok. It also can use this model in the service industry, which meets time-vary customer requirement day after day.