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In order to obtain the optimal scheme of task allocation problem for multiple mobile robots. Considering task allocation problem is a multi-objective optimization problem in essence, a general multi-objective task allocation model is established. A new method named multi-objective optimization genetic algorithm based on decision preference information (DPIMOGA) is proposed to solve the optimal allocation...
Genetic Algorithms (GA) are search and optimization algorithms and as such are used for minimizing or maximizing a given function and if possible finding its most suitable solution. They can be used for finding a solution to problems that are difficult to solve with traditional optimization techniques, including problems that are not well defined or difficult to be mathematically modeled, such as...
Computer games that handle realistic environments are becoming more popular in the game market. Games that make use of natural environments such as the spreading of fire or the flow of water need to be very carefully designed. In order to produce a desired effect of fire or water, a designer needs to try and test map properties several times. There has been an effort to use genetic algorithm to find...
In order to design the products that meet consumer emotional demands, this paper proposes a systematic method which combines neural network with genetic algorithm. Firstly, a back propagation neural network is applied to map the relationships between product design elements and customer kansei image evaluation. Secondly, generic algorithm is employed to search for the optimal product form which satisfies...
Prediction of village electrical load is very important to manage village electrical load efficiently. Support vector regression (SVR) is a new learning algorithm based on statistical learning theory, which has a good time-series forecasting ability. As the choice of the best parameters of support vector regression is an important problem for support vector regression, and this problem will directly...
Methods for the identification of temperature in intelligent building and building equipments is one of hot topics focused by lots of researchers in that research area. To implement the process of inspecting and forecasting of energy efficiency in building and its accessory, a feed forward neural network is used as the identification structure for temperature identification of internal space in building...
Time series forecasting is the main method in network flow prediction. RBF neural network is capable of universal approximation, which not only has fast training velocity, but also can solve the local minima problem. Thus, network flow prediction technology based on genetic algorithm and RBF neural network is presented in the paper. And the training parameters are adjusted by genetic algorithm. Network...
A solving method with ant colony system for irregular parts nesting was put forward. A method for an irregular part's graph coding and pretreatment was proposed. The proposed method converted the nesting problem into an orthogonal rectangular nesting problem by combining and filling algorithm. By use of remaining rectangle matching and orthogonal accessing algorithm, an automatic nesting system was...
The multi-echelon inventory control of weapon equipment repairable spare parts is an important problem for equipment support. In this paper, a genetic algorithm for the multi-inventory problem of repairable spare parts was proposed. In the genetic algorithm, a suitable chromosome representation for multi-inventory problem was presented, and the crossover and mutation operators were investigated. To...
Using genetic algorithm and BP neural network method of combining, this paper has established dynamic forward feedback correction model and has completed the automatic adjustment of the various parameters required for rolling steel pipe, and has made rolled steel pipe system work at the best value. After the actual data validation, the model can more accurately pre-adjusted parameters to achieve intelligent...
A heuristic genetic algorithm for multi-mode resource-constrained project scheduling problem is given because the requisition of constraints of using renewable and nonrenewable resource in practical engineering is taken into consideration. Consumption of nonrenewable resource, weighted coefficient and the duration are combined, and objective function is constructed dynamically by choosing different...
Multi-objective optimization(MOO) has become an important research area of evolutionary computation in recent years,and the current research work focuses on the Pareto optimal-based MOO evolutionary approaches. The research objectives of multi-objective evolutionary algorithms is to make the populations fast convergence and evenly distributed in the question of the optimal noniferior domain. The paper...
A messy genetic algorithm (mGA), speculated by David Goldberg in 1989, is regarded as one of the most efficient method on those problems with Building Blocks (BB). While Hierarchical-if-and-only-if (HIFF) test problem is the basic example of a hierarchically consistent building-block problem. As it features hierarchical BB structure with multiple optima, HIFF test problem becomes the hardest test...
This paper presents a model which generates architectural layout for a single flat having regular shaped spaces; Bedroom, Bathroom, Kitchen, Balcony, Living and Dining Room. Using constraints at two levels; Topological (Adjacency, Compactness, Vaastu, and Open and Closed face constraints) and Dimensional (Length to Width ratio constraint), Genetic Algorithms have been used to generate the topological...
Cutting stock is concerned with how to saving material, optimize resources in product designing, manufacturing. It is very complicated and difficult in computing theory, but it has got the extensive application in the actual manufacture. In allusion to the actual characteristics of the genetic algorithm which is applied in the problem of the optimization in rectangular pieces of material, this paper...
Container stowage problem with multi-restrictions is a complicated combinatorial optimization problem. It's difficult to obtain an optimal solution. Considering many restrictions in practical applications, an improved genetic algorithm for the optimization of container stowage problem is presented in this paper. Experiment results show that the proposed algorithm is feasible and effective, and can...
The problem of end effects in Hilbert-Huang transform is produced in the Empirical Mode Decomposition (EMD), which has a badly effect on Hilbert-Huang transform. In order to overcome this problem, multi-objective Genetic Algorithm (GA) for solving the parameters selection of RBF Neural Network (RBF_NN) (GRHHT) is presented in this paper. Then the RBF_NN is used to predict the signal before EMD. The...
In the paper a novel improved genetic algorithm is proposed based on the maximum entropy for thresholding image segmentation. First of all, the encoded mode is made and the maximum entropy function is selected as the key adaptation genetic algorithm, and then the initial group is generated by roulette selection algorithm to the next generation for the best individual, which can improve the global...
Gait recognition is of increasing interest recently. A gait recognition method using the temporal information of leg angles is proposed, based on the fact that changes of leg angles can reflect main trait of a man's moving. First the pendulum model is referred to for extracting leg parts, and least-square method is used for boundary fitting, to obtain the temporal information of angle about thigh...
Mutation Testing is used as fault-based testing to overcome limitations of other testing approaches but it is recognized as expensive process. In mutation testing, a good test case is one that kills one or more mutants, by producing different mutant output from the original program. Evolutionary algorithms have been proved its suitability for reducing the cost of data generation in different testing...
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