TY - JOUR
T1 - Multi-directional maximum-entropy approach to the evolutionary design optimization of water distribution systems
AU - Saleh, Salah H. A.
AU - Tanyimboh, Tiku T.
PY - 2016/4/30
Y1 - 2016/4/30
N2 - A new multi-directional search approach that aims at maximizing the flow entropy of water distribution systems is investigated. The aim is to develop an efficient and practical maximum entropy based approach. The resulting optimization problem has four objectives, and the merits of objective reduction in the computational solution of the problem are investigated also. The relationship between statistical flow entropy and hydraulic reliability/failure tolerance is not monotonic. Consequently, a large number of maximum flow entropy solutions must be investigated to strike a balance between cost and hydraulic reliability. A multi-objective evolutionary optimization model is developed that generates simultaneously a wide range of maximum entropy values along with clusters of maximum and near-maximum entropy solutions. Results for a benchmark network and a real network in the literature are included that demonstrate the effectiveness of the procedure.
AB - A new multi-directional search approach that aims at maximizing the flow entropy of water distribution systems is investigated. The aim is to develop an efficient and practical maximum entropy based approach. The resulting optimization problem has four objectives, and the merits of objective reduction in the computational solution of the problem are investigated also. The relationship between statistical flow entropy and hydraulic reliability/failure tolerance is not monotonic. Consequently, a large number of maximum flow entropy solutions must be investigated to strike a balance between cost and hydraulic reliability. A multi-objective evolutionary optimization model is developed that generates simultaneously a wide range of maximum entropy values along with clusters of maximum and near-maximum entropy solutions. Results for a benchmark network and a real network in the literature are included that demonstrate the effectiveness of the procedure.
KW - maximum flow entropy
KW - hydraulic reliability and Redundancy
KW - water distribution system
KW - demand driven analysis
KW - pressure driven analysis
KW - penalty-free constrained evolutionary optimization
UR - http://link.springer.com/article/10.1007/s11269-016-1253-6
U2 - 10.1007/s11269-016-1253-6
DO - 10.1007/s11269-016-1253-6
M3 - Article
SN - 0920-4741
VL - 30
SP - 1885
EP - 1901
JO - Water Resources Management
JF - Water Resources Management
IS - 6
ER -