Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach
-
Enso Ikonen
, István Selek and József Bene
This paper examines the application of a particle filtering-based optimization technique, the genealogical decision trees (GDT), to a finite horizon pump scheduling problem in a water distribution network. The GDT approach for trajectory tracking is first introduced, and a modified algorithm for minimization of costs during pump sequence optimization is then presented. Several variants of the algorithm are suggested, using the extended end constraint and neutrality. The performance of the optimization in various algorithm and parameter settings is examined in extensive simulations. It was observed that both the extended end constraint and neutrality improved the performance, however the deviation between solutions within a population and between different runs remained uncomfortably large. Finally, a comparison with a number of alternative up-to-date optimization techniques is provided. It was observed that the performance of GDT was adequate, compared with the best available approaches.
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach
- Response Surface Modeling and Optimization of Immobilized Candida antarctica Lipase-Catalyzed Production of Dicarboxylic Acid Ester
- Search for Optimum Operating Conditions for a Water Purification Process Integrated to a Heat Transformer with Energy Recycling using Artificial Neural Network Inverse Solved by Genetic and Particle Swarm Algorithms
- Generic Mathematical Model for PSA Process
- A Combined Computational Fluid Dynamics and Artificial Neural Networks Model for Distillation Point Efficiency
- Multi-level Reactor Optimisation in the Conceptual Design of Processes with Heterogeneous Catalytic Reactors
- ANN and ANFIS Models for COP Prediction of a Water Purification Process Integrated to a Heat Transformer with Energy Recycling
- Adsorption of Cadmium on Gel Combustion Derived Nano ZnO
- Smith Predictor Based Parallel Cascade Control Strategy for Unstable Processes with Application to a Continuous Bioreactor
- Application of box-behnken design to the extraction of flavonoid fraction of Schizophyllum commune and the empirical kinetic study
- Sewage Sludge to Energy - A Simulation Study
- A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models
- Particle swarm optimization technique for the optimal design of shell and tube heat exchangers
- Neural Network Based Multi Stage Modelling of Chylla Haase Polymerization Reactor
Articles in the same Issue
- Article
- Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach
- Response Surface Modeling and Optimization of Immobilized Candida antarctica Lipase-Catalyzed Production of Dicarboxylic Acid Ester
- Search for Optimum Operating Conditions for a Water Purification Process Integrated to a Heat Transformer with Energy Recycling using Artificial Neural Network Inverse Solved by Genetic and Particle Swarm Algorithms
- Generic Mathematical Model for PSA Process
- A Combined Computational Fluid Dynamics and Artificial Neural Networks Model for Distillation Point Efficiency
- Multi-level Reactor Optimisation in the Conceptual Design of Processes with Heterogeneous Catalytic Reactors
- ANN and ANFIS Models for COP Prediction of a Water Purification Process Integrated to a Heat Transformer with Energy Recycling
- Adsorption of Cadmium on Gel Combustion Derived Nano ZnO
- Smith Predictor Based Parallel Cascade Control Strategy for Unstable Processes with Application to a Continuous Bioreactor
- Application of box-behnken design to the extraction of flavonoid fraction of Schizophyllum commune and the empirical kinetic study
- Sewage Sludge to Energy - A Simulation Study
- A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models
- Particle swarm optimization technique for the optimal design of shell and tube heat exchangers
- Neural Network Based Multi Stage Modelling of Chylla Haase Polymerization Reactor