At present, the successful operations of the fourth party logistics (4PL) in practice gradually demonstrate that it is an effective mode to integrate the supply chain’s complicated resources rationally, efficiently a...
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ISBN:
(纸本)9781424415304;1424415306
At present, the successful operations of the fourth party logistics (4PL) in practice gradually demonstrate that it is an effective mode to integrate the supply chain’s complicated resources rationally, efficiently and flexibly. In order to thoroughly analyze the supply chain resources integration problem in 4PL from a quantitative perspective and to guide the integration practice, based on the previous study results, this paper takes the multi-objectiveoptimization action of the integration decision as an analysis pivot, builds a improved ant algorithm to resolve the integration decision optimization process. Finally, the reasonability and feasibility of the algorithm are validated through the simulation of a calculation case.
Dialogue models have extensive applications and attracted significant attention. However, in the field of hyperparameter optimization, previous methods often face challenges such as prolonged processing time and low a...
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ISBN:
(纸本)9798350387780;9798350387797
Dialogue models have extensive applications and attracted significant attention. However, in the field of hyperparameter optimization, previous methods often face challenges such as prolonged processing time and low accuracy. This study explores a method for optimizing hyperparameters of multi-round dialogue models based on a multi-objective optimization algorithm. Inspired by the evolutionary laws in nature. It proposes a multi-objective evolutionary algorithm capable of dynamically allocating computational resources. It can optimize the hyperparameters of multi-round dialogue models, thereby enhancing the model's accuracy. A highly accurate multi-turn dialogue system can quickly complete the tedious work for people, thereby improving people's quality of life. Compared with the existing work, our method demonstrates shorter processing time and higher accuracy via experiments.
作者：
Wu, ZhanhongYang, CuiliBeijing Univ Technol
Fac Informat Technol Engn Res Ctr Intelligent Percept & Autonomous Con Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China
In this paper, a new approach for optimizing the structure and prediction error of echo state network (ESN) is proposed. ESN is a kind of recurrent neural network with simple training and strong generalization ability...
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ISBN:
(纸本)9781665478960
In this paper, a new approach for optimizing the structure and prediction error of echo state network (ESN) is proposed. ESN is a kind of recurrent neural network with simple training and strong generalization ability. Reservoir is an important structure of ESN, which determine network performance. Thus, multi-objective optimization algorithm is used to optimize network structure and training error simultaneously. Moreover, a local search algorithm based on l(1) regularization is used to accelerate convergence. The experiment results of time series prediction and standard classification show that MESN can improve the network prediction performance while sparse network structure.
In view of the improved algorithm MOEA/D-AU based on the framework of the decomposition based multiobjectiveoptimizationalgorithm framework (MOEA/D), an adaptive dynamic selection angle adjustment strategy is intro...
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ISBN:
(纸本)9781728100159
In view of the improved algorithm MOEA/D-AU based on the framework of the decomposition based multiobjectiveoptimizationalgorithm framework (MOEA/D), an adaptive dynamic selection angle adjustment strategy is introduced to balance between convergence and diversity. This paper proposed an adaptive angle selection multi-objective optimization algorithm, MOEA/D-AAU. The algorithm adaptively adjusts the angle range selection coefficient G in the MOEA/D-AU algorithm by using the appropriate dynamic adjustment strategy, which makes the algorithm focus on the convergent back propagation dispersion in the convergence process. Finally, the performance of proposed algorithm is compared with four the state of the art algorithms on DTLZ and WFG benchmark function. Experiments result demonstrated that MOEA/D-AAU algorithm can achieve better Pareto-optimal solutions and obtain a good convergence and diversity in solution space.
Higher order mutation testing is considered a promising solution for overcoming the main limitations of first order mutation testing. Strongly subsuming higher order mutants (SSHOMs) are the most valuable among all ki...
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ISBN:
(数字)9783319179964
ISBN:
(纸本)9783319179964;9783319179957
Higher order mutation testing is considered a promising solution for overcoming the main limitations of first order mutation testing. Strongly subsuming higher order mutants (SSHOMs) are the most valuable among all kinds of higher order mutants (HOMs) generated by combining first order mutants (FOMs). They can be used to replace all of its constituent FOMs without scarifying test effectiveness. Some researchers indicated that searching for SSHOMs is a promising approach. In this paper, we not only introduce a new classification of HOMs but also new objectives and fitness function which we apply in multi-objective optimization algorithm for finding valuable SSHOMs.
a design method of adaptive fuzzy controllers for Brushless DC motors by applying an improved multi-objective optimization algorithm is proposed. The proposed optimizationalgorithm can optimize and determine the fuzz...
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ISBN:
(纸本)9781467371896
a design method of adaptive fuzzy controllers for Brushless DC motors by applying an improved multi-objective optimization algorithm is proposed. The proposed optimizationalgorithm can optimize and determine the fuzzy rules and membership functions parameters of fuzzy controllers simultaneously in the optimizing, and reconcile the demands of more than one conflicting dynamic and stationary performances. In order to maintain the diversity of individuals to avoid premature mature in the proposed multi-objective optimization algorithm, a new enhancement mechanism is proposed. Simulation experimental results show the designed adaptive fuzzy controllers have stronger robustness and resisting disturbance ability. At the same time, the designed fuzzy adaptive controllers have satisfactory dynamic and stationary performances for Brushless DC motors speed control.
Electricity load prediction is of great significance to the development of the power market and stable operation of power systems. In recent years, scholars in this field have only considered point forecasting, which ...
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Electricity load prediction is of great significance to the development of the power market and stable operation of power systems. In recent years, scholars in this field have only considered point forecasting, which ignores the inevitable prediction bias and uncertain information. To fill this gap, this study proposes an interval prediction system consisting of an advanced data reconstruction strategy, a multi-objective optimization algorithm based on the theory of non-negative constraints, and an outstanding interval forecasting model fitted by the predicted fluctuation characteristics. Moreover, this study theoretically proves that the weight assigned by the optimizationalgorithm is the Pareto optimal solution. Empirical data with 30 min intervals from Queensland, Australia are selected as samples for research. The results not only demonstrate the superiority of the proposed model but also provide effective technical support for power grid operation and dispatch by quantifying changes in the prediction results caused by uncertainties.
The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, gr...
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The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, greenhouse gas emissions and energy efficiency levels of lighting and air conditioning system, according to the mandatory technical regulation in public buildings in Brazil. Presenting a solution to assist in the decision making of engineers, architects or building managers for the optimal arrangements' choice for lighting and air conditioning equipment, considering each built environment and project profile. For the validation process, a basic building was created with 15 rooms spread over three floors, according to the most common construction parameters in the North of Brazil. First, different combinations of objective-function candidates were investigated to compose the multi-objectivealgorithm fitness function, analyzing its performance in two central scenarios: (1) adding some "baits" in air conditioning equipment files, and (2) without this inclusion. Thus, it was found that considering only three objective functions-incremental cost, energy consumption and the air conditioning energy efficiency coefficient-it is possible to get optimal non-dominated solutions in both scenarios, thus highlighting the robustness of the proposed methodology.
Small underwater vehicles have unique advantages in ocean exploration. The resistance and volume of a vehicle are key factors affecting its operation time underwater. This paper aims to develop an effective method to ...
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Small underwater vehicles have unique advantages in ocean exploration. The resistance and volume of a vehicle are key factors affecting its operation time underwater. This paper aims to develop an effective method to obtain the optimal hull shape of a small underwater vehicle using Kriging-based response surface method (RSM) and multi-objective optimization algorithm. Firstly, the hydrodynamic performance of a small underwater vehicle is numerically investigated using computational fluid dynamics (CFD) method and the value range of related design variables is determined. The mesh convergence is verified to ensure the accuracy of the calculation results. Then, by means of the Latin hypercube sampling (LHS) design of simulation, the Kriging-based RSM model is developed according to the relation between each design variable of the vehicle and the output parameters applied to the vehicle. Based on the Kriging-based RSM model, the optimal hull shape of the vehicle is determined by using Screening and MOGA. As results, the vehicle resistance reduces and volume increases obviously.
Oil production and consumption is of great importance for the sustainable development and management of energy and environment. The forecasting of oil imports dependence caused by the gap between production and consum...
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Oil production and consumption is of great importance for the sustainable development and management of energy and environment. The forecasting of oil imports dependence caused by the gap between production and consumption is particularly crucial in the strategic deployment of oil development. However, researches on oil import dependence forecasting are often limited by the small size of data samples and assumptions, and the previous single-objectiveoptimizationalgorithms only focus on the improvement of forecasting accuracy but ignore the stability. Therefore, in order to overcome the shortcomings of researches, in this paper, a hybrid forecasting system for oil imports dependence forecasting based on fuzzy time series and multi-objective optimization algorithm is proposed considering the accuracy and stability simultaneously to achieve the balance and optimality and bridge the limitations of small sample forecasting. The proposed forecasting system is compared with other small sample forecasting models and the fuzzy times series model with traditional interval partition methods. The results show that the proposed system is superior to the traditional methods in all indicators for oil import dependence forecasting. Otherwise, the out of sample forecasting results provided in our research indicate that the oil import dependence will maintain an upward trend, but the rate of increase will slow down. The research results can not only provide the basis for the planning and control of oil import and safety, but also benefit the perceptions of oil price trend in the world energy market and the adjustment of energy market structure.
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