This paper presents a Multi-objective Evolutionary Algorithm (MOEA) to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multiobjective optimization is to find a set of well distributed optimal solutions along the Pareto front. Classical optimization methods often fail in attaining a good Pareto front. To overcome the drawbacks faced by the...

In the multi objective problems, the good Pareto optimum solutions should have the following characteristics; the solutions should be close to the real Pareto front, the solutions should not be concentrated but should be widespread and the solutions should have the optimum solutions of every single objective function. ”Distributed Cooperation model of Multi-Objective Genetic Algorithm (DCMOGA)”...

Multiple objective genetic algorithms (MOGA) are heuristics that have seen relatively little use in geographic information science and spatial decision support in comparison to other geocomputational methods, despite their potential to generate robust alternative options for decision making. MOGA based decision analysis relieves the burden of a priori preference specification by an analyst, but...

Recently, a lot of studies on Multi-Objective Genetic Algorithm (MOGA), in which Genetic Algorithm is applied to Multi-objective Optimization Problems (MOPs), have been reported actively. MOGA has been also applied to engineering design fields, then it is important not only to obtain Pareto solutions having high performance but also to analyze the obtained Pareto solutions and extract the knowl...

This paper considers a flowshop scheduling problem of a manufacturing cell that contains families of jobs whose setup times are dependent on the manufacturing ............ sequence of the families. Two objectives, namely the makespan and total flow time, have been considered simultaneously in this work. Since minimization of each of these two objectives is an NpHard problem, a Multi-Objective G...

In allusion to remove Racian noise while lessen the loss of details as low as possible, this paper proposed an filter algorithm which comprehensive utilize Multi-Objective Genetic Algorithm (MOGA) and Shearlet transform based on a Multi-scale Geometric Analysis (MGA) theory. First, it performs a wavelet multi-scale decomposition of image. Then, it builds target function in MOGA by several evalu...

This paper presents a novel multi-objective genetic algorithm (MOGA) based on the NSGA-II algorithm, which uses metamodels to determine optimal sampling locations for installing pressure loggers in a water distribution system (WDS) when parameter uncertainty is considered. The new algorithm combines the multi-objective genetic algorithm with adaptive neural networks (MOGA–ANN) to locate pressur...

This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating co...

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy) of live VM migration for power saving and load balanc...