Calibration of water distribution network model is of paramount importance for the optimal management of water delivery systems. This includes the determination of network parameters such as pipe roughness coefficients and nodal demands. The parameters are not often exactly known and very much sensitive to the age of the pipe. The calibration is usually accomplished by mimicking the model resul...

Hydrologic Simulation Program-Fortran (HSPF) model calibration is typically done manually due to the lack of an automated calibration tool as well as the difficulty of balancing objective functions to be considered. This paper discusses the development and demonstration of an automated calibration tool for HSPF (HSPF-SCE). HSPF-SCE was developed using the open source software “R”. The tool empl...

The Shuffled Complex Evolution—University of Arizona (SCE-UA) is a classical algorithm in the field hydrology and water resources, but it cannot solve constrained optimization problems directly. Using penalty functions has been preferred method to handle constraints, appropriate selection parameters can be challenging. To enhance universality SCE-UA, we propose Constrained Evolution Algorithm (...

This paper describes a method for scheduling large-scale hydrothermal power systems based on the shuffled complex evolution (SCE-UA) method. A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is also taken into account. SCE-UA is a succes...

The Shuffled Complex Evolution (SCE-UA) has been used extensively and proved to be a robust and efficient global optimization method for the calibration of conceptual models. In this paper, we propose two enhancements to the SCE-UA algorithm, one to improve its exploration and another to improve its exploitation capability of the search space. A strategically located initial population is used ...

Global optimization methods linked with simulation models are widely used for automated calibration and serve as useful tools for searching for cost-effective alternatives for environmental management. A genetic algorithm (GA) and shuffled complex evolution (SCE-UA) algorithm were linked with the Long-Term Hydrologic Impact Assessment (L-THIA) model, which employs the curve number (SCS-CN) meth...

A novel multisite cascading calibration (MSCC) approach using the shuffled complex evolution–University of Arizona (SCE-UA) optimization method, developed at the University of Arizona, was employed to calibrate the variable infiltration capacity (VIC) model in the Red River Basin. Model simulations were conducted at 35 nested gauging stations. Compared with simulated results using a priori para...

In this research, a flood control operating strategy is developed based on simulation-optimization model to reduce damage downstream of multi-reservoir systems by using spillway gates. For purpose, an optimization algorithm introduced, in which the maximum water level points and hydropower potential generation season are objective functions, stages gates decision variables. A global tool, Shuff...

In this research, a study was carried out to exploit the hybrid schemes combining two classical local search techniques i.e. Nelder–Mead simplex search method and bidirectional random optimization with two metaheuristic methods i.e. the shuffled frog leaping and the shuffled complex evolution, respectively. In this hybrid methodology, each subset of meta-heuristic algorithms is improved by a hy...

Recent studies have witnessed remarkable merits of metaheuristic algorithms in optimization problems. Due to the significance early analysis thermal load energy-efficient buildings, this work introduces and compares four novel optimizer techniques—the firefly algorithm (FA), optics-inspired (OIO), shuffled complex evolution (SCE), teaching–learning-based (TLBO)—for an accurate prediction heatin...