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In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model,...
In this study, a new artificial neuron network model called the meta-controlled Boltzmann machine is introduced. The meta-controlled Boltzmann machine model includes the McCulloch-Pitts model, the Hop field network, and also the Boltzmann machine. The proposed method are applied both diffusion processes and simulated annealing. The convergence proof of the proposed method is shows in this paper. Meta-controlled...
Standard CLA-EC which is introduced recently is an evolutionary computing model obtained by combining cellular learning automata (CLA) model and evolutionary computing (EC) model. Some drawbacks of this model are low convergence speed and low accuracy for some optimization problems. In this paper a new version of CLA-EC called Continuous Action Set CLA-EC or in short Continuous CLA-EC is proposed...
Coal or rock electromagnetic emission analysis is a promising method for predicting coal or rock dynamic disasters. Hidden Markov Model (HMM) is applied to this problem in this paper. HMM model is a processing method of dynamic information based on probability, which can reflect both randomicity and potential structure of the object. Model selecting of HMM Bayes Information Criterion is combined with...
In order to solve the strategy optimization of Laser weapon intercept multiple in flight targets problem, a reasonable model is constructed and an improved Genetic Algorithm(GA) is proposed. It introduces both global search strategy and local search strategy to ensure the searching breadth as well as the solution precision. It adds a local search process in the standard GA. When the best child of...
Community mining has been the focus of many recent efforts on complex networks, and the genetic algorithm with low time-complexity is widely used in this discipline. To enhance the performance of genetic algorithm for community detection, the modified crossover operators which are more suitable for community detection is proposed in this paper, and the heuristic mutation operator based on local modularity...
An approach is proposed to obtain global and near-global optimal process plans based on genetic algorithm. During the procedure of initializing and mutating populations, operations precedence constraints are employed by constraint adjustment algorithm to ensure each chromosome stays in feasible domain. Operations precedence constraints can be generated automatically from the selected alternative machining...
Immune Genetic Algorithm-based Load Balancing (IGALB) was proposed to improve the efficiency of search quality and the poor performance of local search in the Simple Genetic Algorithm-based Load Balancing (SGALB). This algorithm ensured the diversity of population and overcame the SGALB premature convergence by carrying out the affinity and concentration calculations. Meanwhile under certain conditions...
This paper investigates the 0-1 knapsack problem using genetic algorithms. The work is based on heuristic strategies that takes into account the characteristics of 0-1 knapsack problem. In this article, a heuristic Genetic Algorithms(GA) is proposed to solve the 0-1 knapsack problem, in each generation, populations are divided into two sections: superior clan and inferior clan, and excellent schema...
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...
A novel application to the optimization of neural networks is presented in this paper. Here, the weight and architecture optimization of neural networks can be formulated as a mixed-integer optimization problem. And then a mixed-integer evolutionary algorithm (Mixed-Integer Hybrid Differential Evolution, MIHDE) is used to optimize the neural network. Finally, the optimized neural network is applied...
A projective point matching algorithm based on modified particle swarm optimization is presented. In the paper, the point matching problem turns into an optimization with two series of parameters, projective transform parameters and correspondent mapping parameters. Firstly, a modified particle swarm optimization (PSO) is introduced and a new rule searching for correspondences, closer point matching...
In DTNs, due to the unique characteristic of frequent partitioning, multicasting is a considerably different and challenging problem. Moreover, the single data multicast is different from multiple data multicast. In this paper, The mathematics model of multiple data multicast for DTNs is established, and the ant colony optimization algorithm introduce to solve the multiple data multicast problem....
A small-signal model is used to design the controller parameters of the conventional Power Factor Correction (PFC) converter. The dynamics of the converter is nonlinear, therefore, it is hard to derive desirable performance. Genetic algorithm is used to optimize the control parameters of PFC converter in this paper, by this way, the quasi-optimal control parameters can be obtained with the predefined...
Ant colony optimization (ACO) is a new evolvement algorithm that is proposed by Dorigo M., and solves some task allocation and target search problems to program the motion path searching food. The topic of the article uses the ant colony optimization algorithm to mobile robot system, and solve the problem of mobile robot path planning such that the target point in a collision free space. The simulated...
Calculating the minimum (or maximum) value of functions is an important problem in optimization field. Applying the method of ant colony optimization (ACO) to solve the problem is an interesting research topic currently, and the main disadvantage is that solution is local optimal. To evade this disadvantage in some degree, in this paper, the ant feature of sensation is used. Experiment shows that...
Delay tolerant networks (DTNs) are a class of emerging networks that experience frequent and long-duration partitions. Multicast supports the distribution of data to a group of users, a service needed for many potential DTN applications, due to the unique characteristic of frequent partitioning in DTNs, multicasting in DTNs is a considerably different and challenging problem. In this paper, The mathematics...
It is a trend for paradigms of nature-inspired computing to hybrid. Inspired by the principle of immune response in the immune system, a novel incremental data clustering algorithm called IRA was proposed in previous work. It obtains high quality clustering. However, the number of clusters obtained by IRA is more than the actual ones. Therefore, the clustering algorithm based on ant colony called...
In this paper, a communication strategy for the parallelized Artificial Bee Colony (ABC) optimization is proposed for solving numerical optimization problems. The artificial agents are split into several independent subpopulations based on the original structure of the ABC, and the proposed communication strategy provides the information flow for the agents to communicate in different subpopulations...
A single-crank-double-rocker mechanism is used to realize the flapping motion of Micro flapping aerial vehicle. However, this vehicle often pitches toward left or right and crashes during flight which mainly caused by the incomplete symmetry of wings movement. To solve this problem, mathematical models of the flapping angle and angular velocity of two wings are established, respectively. An optimal...
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