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Redescription mining aims at finding pairs of queries over data variables that describe roughly the same set of observations. These redescriptions can be used to obtain different views on the same set of entities. So far, redescription mining methods have aimed at listing all redescriptions supported by the data. Such an approach can result in many redundant redescriptions and hinder the user's ability...
This paper proposes a novel optimization scheme by hybridizing an artificial bee colony optimizer (HABC) with a bee life-cycle mechanism, for both stationary and dynamic optimization problems. The main innovation of the proposed HABC is to develop a cooperative and population-varying scheme, in which individuals can dynamically shift their states of birth, foraging, death, and reproduction throughout...
For the production of coal enterprises in new mine after the formation of a strategic alliance, the article takes into account the Union,s overall development strategy of coal resources for a certain period and the interests of the coal enterprises, establishes the alliance production planning model in pursuit of the minimum cost. The application of multi-objective genetic algorithm, each enterprise...
In order to solve the difficulty - how to choose elements of product performance and price - and the distortion problem caused by the multi-variable correlation, this paper proposes a optimized model of product customer satisfaction (PCS) based on genetic algorithms and partial least squares. The model not only solves the distortion problem due to multicollinearity, but also provides multiple models...
Data mining meta-optimization aims to find an optimal data mining model which has the best performance (e.g., highest prediction accuracy) for a specific dataset. The optimization process usually involves evaluating a series of configurations of parameter values for many algorithms, which can be very time-consuming. We propose an agent-based framework to power the meta-optimization through collaboration...
The number of changes that IT departments have to deal with is growing at a fast pace in response to changing business needs of enterprises. As changes are getting executed and deployed, knowledge is being created and stored. It is of paramount importance to the success of the business to re-use that knowledge for future changes. In fact, those who do not learn from past experiences are doomed to...
As a branch of data mining, data classification technology has got a widely use in science, engineering, finance and other areas. The key point of the classification techniques is to construct a classifier, in this paper, a non-liner classifier model based on RBF neural network is introduced to do the data classification, compared with traditional BP neural network, it is not only avoids complicated...
Generally, the environment and enterprises' condition are not stable, in order to promote the enterprises' competitive power, managers must continuously improve the business processes' performance. Based on the simulation method and multi-objective optimization theory, the thesis builds a dynamic multi-objective optimization model for business process optimization. Firstly the framework of optimization...
Based on the optimization problem of the number and size in coal mine equipment the principle and procedure of genetic algorithm is introduced. The case of application proves that the genetic algorithm can better optimize the number and size of equipments in coal mine.
One of the most important phases in business-to-business-based electronic construction bid is the process of bidding decision-making module whose operating optimization is considered to be the foundation of implementing the integration of B2B-based bid mode. Strategies facilitating the optimization of E-bidding are demonstrated in this paper: in order to utilize the efficiency and effectiveness both...
The cellular genetic algorithm with disaster (CDGA) puts individuals into a toridal grid or presudo landscape which behave "active" or "inactive" state. The genetic operator of individuals is restricted to within neighborhood. In this paper, we evaluate combinational effects on size of neighborhood and size of disaster. We have tackled this research by considering two typical functions...
Motivated by the migration mechanisms of ecosystems, various extensions to biogeography-based optimization (BBO) are proposed. BBO is an original optimization method based on the mathematical model of organism distribution in biological systems. BBO is an evolutionary process that achieves information sharing by species migration. This paper generalizes the equilibrium species count in biogeography...
A model of the bee hive that clearly separates the self-organizing decision-making behaviour of the bees in the hive and the problem-specific behaviour of the bees outside the hive is presented. This separation allows for the applications of the model for different problem domains. Results of the application to three problem domains are presented - web search, function optimization and hierarchical...
This paper presents a convex approach for parameter estimation problems (PEPs) involving parameter-affine dynamic systems. By using the available state measurements, the nonconvex PEP is modified such that a convex approximation is obtained. The optimum delivered by this approximation is subsequently used to linearize the original PEP such that a refined solution is obtained. An assessment of the...
The methods of the real estate investment evaluation used today usually fail to solve the high-dimension data. To overcome this shortcoming, an improved PP model was proposed. The method evaluates the merits of the investment programs, according to the size of the projector function by using the Projection Pursuit method. The ant colony algorithm was applied to finish the global optimization. The...
The transport mode and transport path in the multimodal transport have an effect on the benefits of the carriers and customers. According to feature in the relationship between the transport mode selection and the transport path optimization, a integrated model which can be used to select the transport mode and optimize the transport path synthetically was proposed to fit the diversification of the...
This paper presents a new stochastic chance-constrained 0-1 integer programming model for investigating the investment combination problem in multi-project multi-item investment combination. The proposed model includes two objectives with stochastic constraints to construct a 0-1 integer programming model. On the one hand, the risk value will be measured by negative entropy; on the other hand, the...
Business process's performance determine the whole enterprise's economic profit, researching work on business process's optimization is very useful and meaningful. This thesis point out that manager must take the dynamic environment and multiple objectives into account while optimizing the enterprise's business process. Based on the theory of multiple objective optimizations, AHP, and simulation technology,...
According to the relationship of coordinated interaction between unit output and electricity price, an economic/risk/environmental generation optimal model for maximizing total profits in the dealing day and minimizing both risk and emissions was formulated in this paper. A new multi-objective differential evolution optimization algorithm, which integrated Pareto non-dominant sorting and differential...
In this paper, we propose a promising multi-objective (MO) optimization model for partner selection in a market-oriented dynamic collaboration (DC) platform of cloud providers (CPs) to minimize the conflicts among providers that may happen when negotiating among providers. The model not only uses their individual information (INI) but also past collaborative relationship information (PRI) for partner...
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