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With the rapid development of logistics transportation, the number of high-level orderpickers in the warehouse is increasing day by day. In order to improve order picking efficiency, a mathematical model of this optimization problem is constructed according to characteristics of order picking of the high level orderpicker in a rectangular warehouse. To solve the model, G-A (Genetic-Ant colony) algorithm...
The optimization problem that the optimum is time-changing by following a motion law in the search space is a dynamic optimization problem. This paper introduces the optimum's motion information to the proposed algorithms. Particle Filter is used to predict and track the changing optima. In real solution space, GA's chromosome is the same as Particle Filter's particle, both of which can be regarded...
Selective Harmonic Elimination Pulse Width Modulation (SHEPWM) is a well-known Switching Strategy which is applied in multilevel Inverters. The aim of this strategy is eliminating low order harmonics. Basically, harmonic equations are nonlinear and solving them is a major problem for researchers. Evolutionary Algorithms have shown an effective ability for this aim, because they find solution for all...
The Selective Harmonic Elimination Pulse-Width Modulation (SHE-PWM) has been an inclusive research area in the field of Power Converters. This technique offers a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. It involves the solution of non-linear transcendental equation sets representing...
In this paper, a Similarity Reasoning (SR) scheme for monotonic multi-input Fuzzy Inference System (FISs) is proposed. The sufficient conditions for an FIS to be of monotonicity are exploited as part of the SR and FIS modeling procedure. We first assume that the fuzzy membership functions of an FIS are designed according to the sufficient conditions. We then argue that a conventional SR scheme that...
The paper proposes a novel neighborhood search operation of particle swarm in the numerical objective space (eg.Rn), and employs the clonal selection strategy which leads the particle swarm to find the optima of the objective space using the neighborhood search operation. So, a novel particle swarm algorithm based on the clonel selection strategy (NPSA/CS) is proposed. In the test experiment, 6 unconstrained...
Despite of the numerous research efforts on distributed query processing, the complexity of the problem has been little solved which paves way for the exploration on the solution of the problem. However, due to its inherent difficulty, the complexity of the majority of problems on distributed query optimization remains unknown. In this paper, we analyze and present the problems identified and the...
Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed and a heterogeneous in nature. This paper proposes a novel Rank Based Genetic Scheduler...
Optimal Power Flow (OPF) is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming, Newton-Raphson and Non-linear Programming were previously offered to tackle the complexity of the OPF. However, with the emergence of artificial intelligence, many novel techniques...
Premature convergence is the main obstacle to the application of genetic algorithm. This paper makes improvement on traditional genetic algorithm by linear scale transformation of fitness function, using self-adaptive crossover and mutation probability and adopting close relative breeding avoidance method. Simulation results show that the improved algorithm outperforms traditional genetic algorithm...
Blind signal detection by basic ant colony optimization algorithm which is limited to slow convergence speed and local optimum. An improved ant colony optimization algorithm of the direct blind signal detection is proposed in this paper. The algorithm adjusts the pheromone update methods of ant colony algorithm, adds the corresponding parameter control in the local update rule and the global update...
In this paper, for the first time a particle swarm optimization (PSO) method is utilized to optimize placing of wind turbines in a wind park. The location of each wind turbine could be freely adjusted within a predefined cell in order to maximize the generated energy. Simulated results and graphs are carried out to prove that the present study is improved wind farm efficiency and extract more electrical...
This paper describes a genetic algorithm (GA) developed for the reconfiguration of radial distribution systems. The reconfiguration is treated as an optimization problem of combinatory nature, where the aim is to obtain a configuration with minimal power losses, iterations and also with some distribution system restrictions. The initial population of the GA is obtained using spanning trees techniques...
The paper presents application of multiple features for word based document image indexing and retrieval. A novel framework to perform Multiple Kernel Learning for indexing using the Kernel based Distance Based Hashing is proposed. The Genetic Algorithm based framework is used for optimization. Two different features representing the structural organization of word shape are defined. The optimal combination...
An important problem in electrical engineering is to determine the optimal directional overcurrent relay times. The problem is modeled as a constrained nonlinear continuous optimization problem in which the decision variables are the devices that control the act of isolation of faulty lines from the system without disturbing the healthy lines. Two models are considered namely IEEE-3 bus system and...
Optimization problems are ubiquitous and consequential. In fact every sphere of human activity that can be quantified can be formulated as an optimization problem. The focus of this work is on Global Optimization which is not only desirable but also necessary in many cases. In the past few decades several Global optimization algorithms have been suggested in literature out of which stochastic, population...
Heat-supply network is an important part of centralized heat-supply system, and the pipe impedance can affect heat-supply network at many sides. Based on matrix equation of spatial heat-supply network hydraulic calculation method and impedance identification equation, we study the pipe impedance problem in a realistic heat-supply network, which can be transformed into optimization function and solved...
The knapsack problem is formulated as a discrete optimization problem. In this paper, a solution strategy based on an improved binary PSO is presented. It applies new update functions and the strategy of disturbance to deals with the knapsack problem. Furthermore, a penalty function is suggested to change constrained problem into an unconstrained one. The example shows that this algorithm has a faster...
Aiming to the shortages of fuzzy c-means clustering applied to pattern recognition, an improved method by genetic algorithm is proposed. This method can not only automatically optimizes the classification number, but also search the global optimal solution for the clustering center. The experimental results demonstrate this proposed method is excellent for pattern recognition.
According to characteristics of perpendicularity error evaluation of planar lines, particle swarm optimization (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, it can find the global optimal solution, and the precision of calculating...
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