The small parsimony problem is a fundamental discrete optimization problem in computational biology, aiming to find the most parsimonious ancestral labeling over a fixed phylogenetic tree. Classically, the small parsi...
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This paper presents a sustainable optimization model grounded in the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Initially, a comprehensive objective function is formulated, and a cost model is validated. Mo...
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ISBN:
(数字)9798331536169
ISBN:
(纸本)9798331536176
This paper presents a sustainable optimization model grounded in the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Initially, a comprehensive objective function is formulated, and a cost model is validated. Modular analysis of various factors leads to the establishment of optimization criteria focusing on: (1) revenue, (2) carbon footprint, and (3) infrastructure load along with satisfaction level. Corresponding modular models are constructed within the combined objective function, each with distinct constraint conditions. Leveraging Python for computations, the optimal solution is obtained when these objectives are balanced, yielding an optimal quantity of 963,795 units, a revenue of $\mathbf{2 2 3}, 600,584.955$ , an annual carbon footprint of $\mathbf{4 6, 4 4 7. 9 9 2}$ tons, an average annual infrastructure load index of 48.524, and a satisfaction score of $\mathbf{5 3. 5 5 0}$ . The cost model validation results in a cost of $\mathbf{2 6}, \mathbf{4 3 4, 2 0 9}$ , which falls within an acceptable range.
Hybrid digital-analog precoding is a pivotal transmission technique to balance communication performance and hardware costs associated with radio frequency (RF) chains in millimeter wave (mmWave) massive multiple-inpu...
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ISBN:
(数字)9798350368369
ISBN:
(纸本)9798350368376
Hybrid digital-analog precoding is a pivotal transmission technique to balance communication performance and hardware costs associated with radio frequency (RF) chains in millimeter wave (mmWave) massive multiple-input multipleoutput (MIMO). However, most existing designs utilize Shannon rate and assume an infinite blocklength, which is impractical for emerging finite blocklength (FBL) applications, such as massive machine-type communications. To fill in this gap, this paper investigates hybrid precoding optimization in the FBL regime. The aim is to maximize the weighted sumrate (WSR), while fulfilling the transmit power budget at the base station (BS) and users' minimum rate requirements. The formulated optimization problem is highly challenging to solve, particularly due to the complex and nonconcave FBL rate function and the intricate coupling between analog and digital precoders. To tackle these issues, we propose a computationally efficient solution based on the penalty dual decomposition (PDD) method, which is guaranteed to converge to the Karush-KuhnTucker (KKT) solutions under mild conditions. Simulation results demonstrate that our proposed hybrid precoding design significantly outperforms several baseline schemes, especially those ignoring the impact of blocklength and adopting Shannon rate as the performance metric.
This paper addresses modeling and control of traffic flow networks aiming at reduced congestion. We first develop a state-space model of expressing city-level traffic flow controlled by tolling, which is in a class of...
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This paper addresses modeling and control of traffic flow networks aiming at reduced congestion. We first develop a state-space model of expressing city-level traffic flow controlled by tolling, which is in a class of positive systems depending on some designable parameters. Based on the positivity of the model, we next present a design method of optimal tolling in terms of nonlinear programming. The nonlinear programming is transformed into a linear one, which is numerically tractable, by applying the change of variable technique. Finally, the effectiveness of the presented tolling design is shown through a numerical experiment.
This paper presents an efficient preference elicitation framework for uncertain matroid optimization, where precise weight information is unavailable, but insights into possible weight values are accessible. The core ...
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Suppose we are given two metric spaces and a family of continuous transformations from one to the other. Given a probability distribution on each of these two spaces—namely the source and the target measures—the Was...
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Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data discretization and classifi...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data discretization and classification are optimized separately, leading to sub-optimal performance. To tackle the issue, we propose a novel multi-objective optimization framework that incorporates the optimization of the naive Bayes classifier into the objective function of optimizing data discretization. To solve this problem, we employ an alternative optimization method to jointly optimize both data discretization and classification. Additionally, to further enhance the optimization process, we leverage a genetic algorithm to explore and exploit a larger solution space. Experimental results on 20 datasets demonstrate that our method outperforms state-of-the-art methods.
This paper deals with the design of a PSO optimization procedure to tune the LQR and $H_{\infty}$ controller parameters, for the control of the active suspension represented by the quarter car model. The objective is ...
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ISBN:
(数字)9798331541811
ISBN:
(纸本)9798331541828
This paper deals with the design of a PSO optimization procedure to tune the LQR and $H_{\infty}$ controller parameters, for the control of the active suspension represented by the quarter car model. The objective is to create a “skyhook” control and therefore suppress the vertical acceleration of the sprung mass of the vehicle. To validate proposed controller simulation utilizing ISO 8608 road profile is used. The work demonstrates a significant improvement of ride comfort compared to the passive system and gives the comparison of performance of the different control approaches.
The paper proposes a high-dimensional aggregation algorithm for analyzing the objective function in multi-objective location, which is applied to solve the problem of locating new energy facilities. The algorithm cons...
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ISBN:
(数字)9798331520298
ISBN:
(纸本)9798331520304
The paper proposes a high-dimensional aggregation algorithm for analyzing the objective function in multi-objective location, which is applied to solve the problem of locating new energy facilities. The algorithm consists of three steps: Firstly, all facilities within the area are defined as decision variables and their corresponding sub-objective functions are calculated. These decision variables and sub-objective functions are then projected onto facility points in a high-dimensional space, where each dimension corresponds to a sub-objective function value. The Euclidean distance between these high-dimensional facility points reflects the differences among different facilities in the multi-objective optimization environment. Secondly, an n-DFPS (n-dimensional facility point seasonal algorithm) is designed to find the Pareto point in this high-dimensional space by minimizing the sum of Euclidean distances between that point and all other high-dimensional facility points. The facilities are weighted based on their Euclidean distances from both the high-dimensional facility point and the high-dimensional Pareto median point. Finally, all facility points are projected onto weighted facility points on a two-dimensional plane according to their latitude, longitude, and weight information; 2-PGSA (2-dimensional facility point seasonal algorithm) is used to identify Steiner points on this plane as reasonable locations for new energy facilities. To validate its effectiveness, an industrial and commercial energy storage station location case study is conducted using simulation experiments comparing it with classical location algorithms; results demonstrate superiority of our proposed algorithm.
The use of variable-speed electric drives has gained increasing importance due to their enhanced technical performance. To address issues like current ripple, additional motor and cables losses, electromagnetic interf...
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ISBN:
(数字)9798331533946
ISBN:
(纸本)9798331533953
The use of variable-speed electric drives has gained increasing importance due to their enhanced technical performance. To address issues like current ripple, additional motor and cables losses, electromagnetic interference, overvoltage on the stator windings, and acoustic noise of PWM controlled variable-speed electric drives and achieve suitable voltage quality at the motor terminals, the use of a sine wave output filter has become a practical industrial solution. This paper presents the optimal design of a sine wave filter for a medium voltage (MV) induction motor powered by a low switching frequency multilevel inverter. The design process considers resonance and stability issues, and determines the optimal filter structure and components by minimizing the weighted sum of the objective function components. The proposed method utilizes genetic algorithms and component modeling, incorporating objective functions such as voltage total harmonic distortion (THD), current THD, and filter components cost. Constraints, including the voltage drop across the inductor and losses due to damping resistance, are also considered in the optimal filter configuration. The sine wave filter is designed with a reduced ratio of switching frequency to filter resonance frequency $\left(r_{f}\right)$, resulting in a higher resonant frequency of filter and therefore smaller inductance and capacitance, and ultimately better voltage quality for the motor across all operating frequencies. Analysis and simulations have been conducted to validate the proposed design.
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