A study on bacterial evolutionary algorithm engine for interactive nurse scheduling support system

Nurse scheduling problem (NSP) is a combinatorial optimization problem. This paper presents an interactive nurse scheduling support system. This system learns the evaluation criteria from the past schedules, and generates new schedules using the bacterial evolutionary algorithm (BEA). The user can modify or fix parts of the candidate schedules. The system reschedules the parts that need improvement. The proposed system is needed to produce high quality schedules with a short computation time for a good human-machine interaction. This paper examines the BEA operations, and studies the hardware implementation of BEA on field programmable gate array (FPGA). Appropriate operations and parameters of BEA are clarified. A practical NSP was estimated and solved within 2 seconds by the hardware.