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In this paper, we proposed a coevolutionary multi-objective genetic watermarking scheme based on the wavelet packet transform. Wavelet packet transform can be viewed as a generalization of the discrete wavelet transform and a best wavelet basis in the sense of some cost metric can be found within a large library of permissible bases. Coevolutionary multi-objective genetic algorithm is used to select...
In this paper we have proposed a new archive based steady state multi-objective genetic algorithm, which performs well, especially in higher dimensional space. An improved archive maintenance strategy has been introduced in this algorithm which is adaptive as well as dynamic in size. The archive maintenance strategy tries to maintain only the set of nondominated solutions in the archive. However,...
This article introduces asynchronous implementations of selected synchronous cooperative co-evolutionary multi-objective evolutionary algorithms (CCMOEAs). The CCMOEAs chosen are based on the following state-of-the-art multi-objective evolutionary algorithms (MOEAs): Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Multi-objective Cellular...
The multi-objective optimization for k-out-of-n redundancy allocation problem with multiple k-out-of-n subsystems connected in series considering k impacts the cost function is presented. The design objective is to select multiple components for a subsystem to maximize system reliability and minimize system cost while satisfying system requirement constraints. Mixing of non-identical component types...
Cloud design resources scheduling is a critical issue of the cloud design platform. In order to solve this problem, a scheduling model is established, setting cost, time and quality of service as optimization objectives, and considering the service state of cloud design resources as well. In this model, satisfaction of requests and load balancing of resources are constraints. A scheduling algorithm...
The NSGA-II method has been shown highly effective to provide sufficient selection pressure searching towards Pareto optimal set in multi-objective optimization. However, an important drawback in NSGA-II is that the diversity of resulting populations is not satisfactory due to the shortcoming of crowding distance. In this paper, we propose a diversity maintenance strategy for NSGA-II to enhance diversity...
This paper treats a tuning of PID controllers method using Multi-objective Differential Evolution. The objective was to apply the differential evolution algorithm in the aim of tuning the optimum solution of the PID controllers (Kp, Ki and Kd) by minimizing the multi-objective function. The potential of using Multi-objective Differential Evolution is to identify Pareto-optimal solution. A classic...
In this paper, the dynamic model of the glutamic acid fermentation process is established by using the neural network. Combined with satisfaction optimization method, multi-objective and multi-variable optimization for the glutamic acid fermentation process is proceeded with the objects of the production rate of glutamic acid and conversion rate. The paper also set up the corresponding satisfaction...
This paper proposes a modeling of data networks with delay, packet loss ratio and network cost and an optimization of them using genetic algorithm. The network delay is expressed in terms of three delays such as propagation delay, transmission delay and queuing delay of links. The packet loss ratio is defined as the ratio of successful packet transmission to total transmission over a link and the...
In order to further ease the disaster of computing costs in multi-objective optimization problem, we've put forward a kind of multi-objective genetic algorithm based on clustering. The algorithm uses the fuzzy c-means clustering control the similar individuals gathered in a class and for each class construct non-dominated set with arena's principle, so that we can use faster speed to choose the non-dominated...
This paper presents a multi-objective optimization of a Permanent Magnet Assisted Synchronous Reluctance Machine with three barriers per pole, based on a genetic algorithm. The aim of the study is to optimize both the torque and the high frequency electro-magnetic saliency, to obtain a motor with a good behaviour when controlled by means of sensorless techniques with high frequency signal injection...
An open problem in robotics is the one dealing with the way a mobile robot locates itself inside a specific area. The problem itself is vital for the robot to correctly achieve its goals. There are several ways to approach this problem, for example, robot localization using landmarks [4], [5], calculation of the robot's position based on the distance it has covered [6], [7], etc. Many of these solutions...
Path planning problem of mobile robot is one that has intrigued and has received much attention throughout the history of robotics, since it is at the essence of what a mobile robot needs to be considered truly “autonomous”. A mobile robot must be able to find collision-free paths to move from one location to another, and in order to truly show a level of intelligence these paths must be optimized...
Because of its sheer size, Computational Grids (CGs) require advanced methodologies and strategies to efficiently schedule users tasks and applications to resources. Scheduling becomes even more challenging when energy efficiency, classical make span criterion and user perceived Quality of Service (QoS) are treated as first-class objectives in CG resource allocation methodologies. In this paper we...
Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an...
In this paper, the data of the teaching evaluation system is optimized by multi-objective optimization to achieve the purpose of teaching evaluation. The data in the database is a significant reduction in the retrieval process by multi-objective. From the actual results, the data after the multi-objective optimization easy to teaching evaluation, to achieve the desired results.
Shunt active power filter is suitable to compensate current-type harmonics generated by nonlinear load. However which generates high frequency switching harmonic current into the power grid by using the pulse width modulation (PWM) technology. So the switching harmonic filter must be used to eliminate ripple current. Based on the analysis of the working principle of switching harmonic filter, the...
An intelligent voltage control (IVC) system is proposed in this paper. Accompanied with training and learning capabilities, this system can realized a fast and efficient voltage control after an emergency happens in a power system.
In this study, a multi-objective hybrid genetic algorithm (MOHGA) is proposed to optimize a multi-objective imperfect preventive maintenance (MOIPM) model. The MOHGA proposed not only utilizes a Pareto-based technique to determine and retain the superior chromosomes as the GA chromosome evolutions are performed, but also guides their search direction. In order to obtain diverse non-dominated solutions...
In allusion to the multi-piece leaf springs of a truck, its standard multi-objective optimization model was established. Taking multidisciplinary optimization software iSIGHT as a platform, using the non-dominated Sorting Genetic Algorithm (NSGA-II) based on Pareto optimal concepts, seek for the optimal structural design scheme for multi-piece leaf springs of the minimum total quality and minimum...
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