CALIBRATION OF C-TOWN NETWORK USING HARMONY SEARCH ALGORITHM

This study adopts the Harmony Search (HS) meta-heuristic algorithm (Geem et al., 2001; Kim et al., 2001) to calibrate a hydraulic simulation model (EPANET) for C-Town. The algorithm conceptualizes a musical process of searching for a perfect state of harmony (optimal solution) and allows a random search without initial values, thus removing the necessity for information on derivatives. The calibration procedure is implemented in a manner that the sum of errors between two data sets: the measured SCADA data and the values derived from the HS algorithm. The calibration process is implemented into three stages – preprocess, rough tuning, and fine tuning. In the preprocess stage the original SCADA data and pump control rules are modified to complement missing data and operation rules. In the rough and fine tuning stages the C-town network is divided into five sub-networks based on supply zones. Pipe roughness factors in each sub-network are calibrated by pipe diameters which are divided into five groups. Therefore, total number of decision variables in each sub-network is 168 nodal water demand factors and 5 pipe roughness coefficients. The entire C-town network is also calibrated using each already calibrated sub-network as the initial populations. It is found that the simple network in the downstream end can be calibrated separately; thus, the network division does accelerate the convergence speed. Several parameters of the HS algorithm such as HMCR and PAR can be adjusted to find better calibration results