Multiobjective Differential Evolution with Application to Reservoir System Optimization

摘要: Many water resources systems are characterized by multiple objectives. For multiobjective optimization, typically there can be no single optimal solution which simultaneously satisfy all the goals, but rather a set of technologically efficient noninferior or Pareto solutions exists. Generating those is challenging task and often difficulties arise in using conventional methods. In optimization reservoir systems, most times interdependence among one more decision variables. Recently, it emphasized that evolutionary operators used differential evolution algorithms very much suitable for problems having This paper utilizes this aspect presents an effective approach namely (MODE) algorithm with application to case study system optimization. The developed MODE first tested on few benchmark test validated standard performance measures comparing them nondominated sorting genetic algorithm-II. On achieving satisfactory problems, applied generate operation problem. It found provides many alternative uniform coverage convergence true fronts. results obtained show proposed viable generating trade-offs systems.