РОЗРОБКА АЛГОРИТМІВ ПЛАНУВАННЯ РОБОТИ ПЕРСОНАЛУ З ГНУЧКИМ ГРАФІКОМ РОБОТИ.

Гаврилюк, О. І.; Жданова, О. Г.; Сперкач, М. О.

The process of optimization work schedule is important for meeting the needs for staff and requirements of work time standards and also for accounting staff availability and preferences. The paper considers shifts scheduling problems for staff with a flexible work schedule. It was formulated three problems of determining the number of staff, who start to work in a given interval of the day. The problems deal with a given duration of the shift and lunchtime, which can be planned in the given bounds and the given staff number. The objective of the problems is to minimize the total deviation of staff count from needs for them in each time interval during the day. There have been proposed two methods for determining the staff number in each interval, which envisages the solve of the two optimization problems. The problem, in which it is needed to define the number of staff without the count of lunchtime is solving in the first stage of the first method and with the count of lunchtime in given intervals in the first stage of the second method. After the solution of the first stage problem, in both methods, it is needed to assign lunchtime in allowed bounds in the solution got in the previous problem to minimize the total deviation of staff numbers from needs for them. It was got nonlinear problems, which were transformed into the integer linear and binary integer programming problems. There have been developed heuristic algorithms for solving the problem with unfixed lunchtime. There were two series of experiments with the purpose of research their efficiency. The input dataset for experiments was generated randomly in given bounds of interval time. The number of intervals and bounds of flexible lunchtime are variated parameters. The results of experiments prove the efficiency of the first method and the needs of additional research on the second one.

SHIFT systems; WORKING hours; FLEXTIME; NONLINEAR equations; PROCESS optimization; INTEGER programming; HEURISTIC algorithms

Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì, 2019, Vol 9, Issue 3, p144

2223-5744

Academic Journal

10.15276/imms.v9.no3.144