Results in Control and Optimization最新文献

Optimal control analysis of a mathematical model for guava nutrients in an integrated farming with cost-effectiveness 具有成本效益的综合农业中番石榴营养数学模型的优化控制分析

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-11-13 DOI: 10.1016/j.rico.2024.100490

Pulak Kundu, Uzzwal Kumar Mallick

Because of its high nutritional value and easy availability, guava fruit has become more popular as a crop in tropical regions in recent decades. Unfortunately, its cultivation faces multifaceted challenges, with increasing the guava borer due to global warming posing a significant threat to crop yield, while the cost of pesticides adds to the economic burden on farmers. To overcome this difficulty, an integrated cultivation method has been devised to simultaneously cultivate guava and tuberose flowers for the purpose of biological pest management, while also earning money through the sale of the flowers to support the integrated agricultural plan. The present mathematical modeling study has focused on the optimal control problem using the strategy of spraying pesticides and flower harvesting, to achieve the highest possible profit. Characterization of the proposed optimal control was then carried out using Pontryagin’s maximum principle, where the objective of our farming would be higher when optimal management of our strategies would be provided compared to other scenarios. To find the most efficient and least expensive approach, cost-effectiveness analysis has been performed. According to the findings, an optimal strategy for harvesting flowers is the most economical and efficient way to increase the amount of earnings from this integrated farming. However, the results of this study can help the farmers in developing beneficial strategies to gain maximum profit by reducing the cost.

近几十年来，番石榴果实因其营养价值高、易于获取而成为热带地区更受欢迎的作物。遗憾的是，番石榴的种植面临着多方面的挑战，全球变暖导致番石榴蛀虫增加，对作物产量构成重大威胁，而杀虫剂的成本又加重了农民的经济负担。为了克服这一困难，人们设计了一种综合栽培方法，同时栽培番石榴和块茎花，以达到生物病虫害防治的目的，同时还通过销售块茎花赚钱，以支持综合农业计划。本数学建模研究的重点是利用喷洒农药和收获花卉的策略来解决最优控制问题，以实现尽可能高的利润。然后利用庞特里亚金的最大原则对建议的最优控制进行了表征，与其他方案相比，当我们的策略得到优化管理时，我们的农业目标就会更高。为了找到效率最高、成本最低的方法，我们进行了成本效益分析。研究结果表明，最佳的鲜花采摘策略是提高综合农业收益的最经济、最有效的方法。不过，这项研究的结果可以帮助农民制定有利的战略，通过降低成本获得最大利润。

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引用次数: 0

Observer-based fuzzy T–S control with an estimation error guarantee for MPPT of a photovoltaic battery charger in partial shade conditions 基于观测器的模糊 T-S 控制，为部分遮阳条件下光伏电池充电器的 MPPT 提供估计误差保证

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-11-12 DOI: 10.1016/j.rico.2024.100488

Redouane Chaibi , Rachid EL Bachtiri , Karima El Hammoumi , Mohamed Yagoubi

To improve the efficiency and performance of a photovoltaic system (PV) an observer-based fuzzy controller design methodology is provided in the study. The desired controller is achieved by employing a combination of linear matrix inequalities (LMIs). The system consists of a photovoltaic generator (PVG) connected to a boost converter. A battery is linked to the boost converter to stock additional energy for further use. A fuzzy controller based on a T–S fuzzy type observer that guarantees a predefined

L_{2}

performance is suggested to achieve maximum power point tracking (MPPT) even under changing weather conditions. An optimal trajectory should be tracked to ensure maximum power operation. For this aim, a specific reference fuzzy model is proposed to create the aimed trajectories. Using this method, the system dynamics are precisely reproduced over a large range of operations. The whole T–S fuzzy methodology, suggested in this paper, aims to ensure the most efficient energy recovery to recharge a battery under partially shaded conditions, resulting in high system efficiency. The proposed method is simulated with MATLAB /SIMULINK and the simulation results, with realistic reference trajectories, are driven while taking into account climate variations. The analysis of these simulations, along with a comparison with two other commonly used approaches, led to the conclusion that the suggested strategy succeeded in reducing the tracking time, as well as eliminating the oscillation that often occurs around maximum power point (MPP).

为了提高光伏系统（PV）的效率和性能，本研究提供了一种基于观测器的模糊控制器设计方法。通过线性矩阵不等式（LMI）的组合，可实现所需的控制器。该系统由连接到升压转换器的光伏发电机（PVG）组成。蓄电池与升压转换器相连，以储存额外的能量供进一步使用。建议采用基于 T-S 模糊类型观测器的模糊控制器，以保证预定的 L2 性能，从而实现最大功率点跟踪 (MPPT)，即使在不断变化的天气条件下也是如此。应跟踪最佳轨迹，以确保最大功率运行。为此，提出了一个特定的参考模糊模型来创建目标轨迹。利用这种方法，可以在很大的运行范围内精确再现系统动态。本文提出的整个 T-S 模糊方法旨在确保在部分遮光条件下以最高效的能量回收为电池充电，从而实现较高的系统效率。本文利用 MATLAB /SIMULINK 对所提出的方法进行了仿真，仿真结果采用了现实的参考轨迹，同时考虑到了气候的变化。通过对这些仿真结果的分析，以及与其他两种常用方法的比较，得出的结论是，所建议的策略成功地缩短了跟踪时间，并消除了在最大功率点（MPP）附近经常出现的振荡。

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引用次数: 0

Satellite imagery, big data, IoT and deep learning techniques for wheat yield prediction in Morocco 卫星图像、大数据、物联网和深度学习技术用于摩洛哥小麦产量预测

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-11-08 DOI: 10.1016/j.rico.2024.100489

Abdelouafi Boukhris, Antari Jilali, Abderrahmane Sadiq

In the domain of efficient management of resources and ensuring nutritional consistency, accuracy in predicting crop yields becomes crucial. The advancement of artificial intelligence techniques, synchronized with satellite imagery, has emerged as a potent approach for forecasting crop yields in modern times. We used two types of data: spatial data and temporal data. Spatial data are gathered from satellite imagery and processed using ArcGIS to extract data about crops based on several indices like NDVI and NWDI. Temporal data are gathered from agricultural sensors such as temperature sensors, rainfall sensor, precipitation sensor and soil moisture sensor. In our case we used Sentinel 2 satellite to extract vegetation indices. We have used IoT systems, especially Raspberry Pi B+ to collect and process data coming from sensors. All data collected are then stored into a NoSQL server to be analysed and processed. Several machine learning and deep learning algorithms have been used for the processing of crop recommendation system, such as logistic regression, KNN, decision tree, support vector machine, LSTM, and Bi-LSTM through the collected dataset. We used GRU deep learning model for the best performance, the RMSE and R² for this model was 0.00036 and 0.99 respectively.

The main contribution of our paper is the development of a new system that can predict several crop yields, such as wheat, maize, etc., using IoT, satellite imagery for spatial data and the use of sensors for temporal data. We are the first paper that has combined spatial data and temporal data to predict crop yield based on deep learning algorithms, unlike other works that uses only remote sensing data or temporal data. We created an E-monitoring crop yield prediction system that helps farmers track all information about crops and show the result of prediction in a mobile application. This system helps farmers with more efficient decision making to enhance crop production. The main production regions of wheat in Morocco are in the rainfed areas of the plains and plateaus of Chaouia, Abda, Haouz, Tadla, Gharb and Saïs. We studied three main regions well known for wheat production which are Rabat-Salé, Fez-Meknes, Casablanca-Settat.

在有效管理资源和确保营养一致性方面，准确预测作物产量至关重要。人工智能技术与卫星图像同步发展，已成为现代预测作物产量的有效方法。我们使用了两类数据：空间数据和时间数据。空间数据来自卫星图像，并使用 ArcGIS 进行处理，以提取基于 NDVI 和 NWDI 等指数的作物数据。时间数据来自农业传感器，如温度传感器、雨量传感器、降水传感器和土壤水分传感器。在我们的案例中，我们使用哨兵 2 号卫星来提取植被指数。我们使用物联网系统，特别是 Raspberry Pi B+ 来收集和处理来自传感器的数据。收集到的所有数据都会存储到 NoSQL 服务器中进行分析和处理。在处理作物推荐系统时，我们使用了多种机器学习和深度学习算法，如逻辑回归、KNN、决策树、支持向量机、LSTM 和 Bi-LSTM 等。我们使用的 GRU 深度学习模型性能最佳，该模型的 RMSE 和 R2 分别为 0.00036 和 0.99。我们论文的主要贡献是利用物联网、卫星图像获取空间数据，并使用传感器获取时间数据，开发了一种可预测小麦、玉米等多种作物产量的新系统。与其他仅使用遥感数据或时间数据的论文不同，我们是第一篇结合空间数据和时间数据，基于深度学习算法预测作物产量的论文。我们创建了一个电子监测作物产量预测系统，帮助农民跟踪作物的所有信息，并在移动应用程序中显示预测结果。该系统可帮助农民做出更有效的决策，提高作物产量。摩洛哥的小麦主产区位于沙维雅、阿布达、豪斯、塔德拉、加尔布和赛斯平原和高原的雨水灌溉区。我们研究了拉巴特-萨莱、非斯-梅克内斯、卡萨布兰卡-塞塔特这三个著名的小麦主产区。

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引用次数: 0

Selective opposition based constrained barnacle mating optimization: Theory and applications 基于选择性对抗的约束藤壶交配优化：理论与应用

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-26 DOI: 10.1016/j.rico.2024.100487

Marzia Ahmed , Mohd Herwan Sulaiman , Md. Maruf Hassan , Md. Atikur Rahaman , Masuk Abdullah

Mathematical models of Barnacle Mating Optimization (BMO) are based on observations of real-world barnacle mating behaviors such as sperm casting and self-fertilization. Nevertheless, BMO considers penis length to produce new offspring through pseudo-copulated mating behavior, with no constraints like strong wave motion, food availability, or wind direction considered. Exploration and exploitation are two crucial optimization stages as we implement the constrained BMO. They are informed by models of navigational sperm casting properties, food availability, food attractiveness, wind direction, and intertidal zone wave movement experienced by barnacles during mating. We will later integrate opposition-based learning (OBL) with constrained BMO (C-BMO) to improve its exploratory behavior while retaining a quick convergence rate. Rather than opposing all barnacle dimensions, we just opposed those that went over the border. In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.

藤壶交配优化（BMO）的数学模型是基于对现实世界中藤壶交配行为的观察，如撒精和自交。不过，BMO 考虑的是阴茎长度，通过伪繁殖交配行为产生新的后代，而没有考虑强浪运动、食物供应或风向等限制因素。探索和利用是我们实施受限 BMO 的两个关键优化阶段。它们参考了藤壶在交配过程中经历的导航投精特性、食物可得性、食物吸引力、风向和潮间带波浪运动等模型。稍后，我们将把基于对立的学习（OBL）与受限 BMO（C-BMO）结合起来，以改进其探索行为，同时保持快速的收敛速度。我们不反对所有藤壶维度，而只反对那些越界的维度。除了通过减少浪费在探索上的时间来提高效率外，这还增加了偶然发现最优解的可能性。之后，我们在实际案例研究中对它进行了检验，证明它优于现有的最先进算法。

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引用次数: 0

Comparative exploration on EEG signal filtering using window control methods 使用窗口控制方法进行脑电信号滤波的比较探索

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-15 DOI: 10.1016/j.rico.2024.100485

Aruna Pant , Adesh Kumar , Chaman Verma , Zoltán Illés

Electroencephalography (EEG) is used to monitor brain activity. The brain signals consist of different frequency band signals delta, theta, alpha, beta, and gamma waves. The signals are affected by external noise which reduces the quality of the EEG signal due to which it becomes difficult to do further processing of EEG signals like feature extraction or extraction of meaningful features from EEG signal. Therefore, it becomes important to filter the noise from the EEG signal before feature extraction or classification of the EEG signal. The research article presents an overview of different types of windowing filter techniques like Rectangular, Bartlett, Hamming, Hanning, and Kaiser windows applied for finite impulse response (FIR) behavior which is used for EEG signal processing for different brain waves processed in different frequency bands. The comparative analysis is carried out in terms of the response time of brain frequency bands for different windowing filter techniques using the MATLAB 2023 signal processing simulation tool. The novelty of the work lies in estimating minimum latency and appropriate filter selection for various typical EEG waves, since the EEG signals are pre-supposed in the hardware chip design, noise elimination is the first step in high-performance computing applications. The Bartlett window band stop has an optimal response time of 12.666 s for delta waves, a highpass filter with a response time of 16.187 s for theta waves, a bandpass with a response time of 13.122 s for alpha waves, a highpass filter with a response time of 17.866 s for beta waves, and a highpass filter with a response time of 13.797 s for gamma waves. The Barlett window FIR filter is well-suited for EEG applications.

脑电图（EEG）用于监测大脑活动。脑电信号由不同频段的信号δ波、θ波、α波、β波和γ波组成。这些信号会受到外部噪声的影响，从而降低脑电信号的质量，因此很难对脑电信号进行进一步处理，如特征提取或从脑电信号中提取有意义的特征。因此，在对脑电信号进行特征提取或分类之前，过滤脑电信号中的噪声变得非常重要。研究文章概述了不同类型的开窗滤波技术，如矩形窗、巴特利窗、汉明窗、汉宁窗和凯撒窗等，这些技术适用于有限脉冲响应（FIR）行为，用于在不同频段处理不同脑电波的脑电信号处理。使用 MATLAB 2023 信号处理仿真工具对不同窗滤波器技术的大脑频段响应时间进行了比较分析。这项工作的新颖之处在于估算各种典型脑电图波的最小延迟和适当的滤波器选择，因为脑电图信号在硬件芯片设计中是预先假定的，噪声消除是高性能计算应用的第一步。巴特利特窗带阻波器对三角波的最佳响应时间为 12.666 秒，高通滤波器对三角波的响应时间为 16.187 秒，带通滤波器对阿尔法波的响应时间为 13.122 秒，高通滤波器对贝塔波的响应时间为 17.866 秒，高通滤波器对伽马波的响应时间为 13.797 秒。巴利特窗 FIR 滤波器非常适合脑电图应用。

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引用次数: 0

Attitude control of UAV bicopter using adaptive LQG 利用自适应 LQG 控制无人机双旋翼的姿态

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-11 DOI: 10.1016/j.rico.2024.100484

Fahmizal , Hanung Adi Nugroho , Adha Imam Cahyadi , Igi Ardiyanto

This paper aims to design a controller that is able to maintain the stability of the unmanned aerial vehicle (UAV) bicopter attitude when carrying a payload. When the value of the payload inertia is in uncertainty, it is necessary to design a controller that can carry out the adaptation process. This paper proposes an Linear Quadratic Gaussian (LQG) adaptive controller to control the attitude of the bicopter with uncertain payload conditions. The proposed adaptive mechanism is a development of LQG control that can follow the response of the reference model. The success of LQG adaptive control is tested by providing uncertain payload parameters. The simulation results show that the LQG adaptive controller successfully overcomes the influence of inertial disturbances originating from the payload. There is a gain

ρ

in the LQG adaptive mechanism, this gain is influenced by the parameter

σ

which acts as a learning rate that produces a response to adapt to the response of the reference model. From the test results obtained when the value of

σ

is enlarged there is an increased overshoot condition/value but the root mean square error (RMSE) value decreases. That means when the RMSE decreases, the response is getting closer to the model reference. To reduce the overshoot effect of increasing the value of

σ

, an improvement is made in the search for the gain value of

ρ

. From the test results, the value of

σ = 1

was chosen with the development of the gain equation

ρ

.

本文旨在设计一种控制器，能够在携带有效载荷时保持无人驾驶飞行器（UAV）双旋翼飞行器姿态的稳定性。当有效载荷的惯性值不确定时，有必要设计一种能够执行适应过程的控制器。本文提出了一种线性二次高斯（LQG）自适应控制器，用于在有效载荷不确定的情况下控制双旋翼飞行器的姿态。所提出的自适应机制是对 LQG 控制的发展，它可以跟随参考模型的响应。通过提供不确定的有效载荷参数，检验了 LQG 自适应控制的成功性。仿真结果表明，LQG 自适应控制器成功地克服了来自有效载荷的惯性干扰的影响。在 LQG 自适应机制中有一个增益 ρ，该增益受参数 σ 的影响，参数 σ 作为学习率产生响应，以适应参考模型的响应。从测试结果来看，当 σ 值增大时，过冲条件/值会增加，但均方根误差（RMSE）值会减小。这意味着当 RMSE 值减小时，响应会越来越接近模型参考值。为了减少增大 σ 值带来的过冲效应，对增益 ρ 值的搜索进行了改进。

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引用次数: 0

Optimality results for nondifferentiable multiobjective fractional programming problems under E-B-invexity E-B-invexity 条件下无差别多目标分式程序设计问题的最优性结果

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-11 DOI: 10.1016/j.rico.2024.100486

Dhruv Singh , Shashi Kant Mishra , Pankaj Kumar , Abdelouahed Hamdi

In this article, we study nonconvex multiobjective fractional programming problems involving E-differentiable functions (MFP

_{E}

). We establish the E-Karush–Kuhn–Tucker (E-KKT) sufficient E-optimality conditions for nonsmooth vector optimization problems under the assumption of E-B-invexity. To demonstrate the validity of the derived results, we provide an example where the involved functions exhibit E-B-invexity.

本文研究了涉及 E-可变函数（MFPE）的非凸多目标分数编程问题。在 E-B-invexity 假设下，我们建立了非光滑矢量优化问题的 E-Karush-Kuhn-Tucker (E-KKT) 充分 E-optimality 条件。为了证明推导结果的有效性，我们提供了一个例子，其中涉及的函数表现出 E-B-inxxity 特性。

引用次数: 0

Hybridized Brazilian–Bowein type spectral gradient projection method for constrained nonlinear equations 约束非线性方程的混合巴西-伯温型谱梯度投影法

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-10 DOI: 10.1016/j.rico.2024.100483

Jitsupa Deepho , Abdulkarim Hassan Ibrahim , Auwal Bala Abubakar , Maggie Aphane

This paper proposes a hybridized Brazilian and Bowein derivative-free spectral gradient projection method for solving systems of convex-constrained nonlinear equations. The method avoids solving any subproblems in each iteration. Global convergence is established under appropriate assumptions on the functions involved. Additionally, numerical experiments are conducted to evaluate the algorithm’s performance, providing evidence of its efficiency compared to similar algorithms from the existing literature. The results demonstrate that the method outperforms some existing approaches in terms of the number of iterations, function evaluations, and time required to obtain a solution based on the examples considered.

本文提出了一种混合巴西法和伯温无导数谱梯度投影法，用于求解凸约束非线性方程系统。该方法避免在每次迭代中求解任何子问题。在对相关函数进行适当假设的情况下，确定了全局收敛性。此外，还进行了数值实验来评估该算法的性能，以证明其与现有文献中类似算法相比的效率。结果表明，根据所考虑的示例，该方法在迭代次数、函数评估以及获得解决方案所需的时间方面都优于一些现有方法。

引用次数: 0

Spatiotemporal dynamics of toxin producing phytoplankton–zooplankton interactions with Holling Type II functional responses 产生毒素的浮游植物与浮游动物相互作用的时空动态与霍林 II 型功能反应

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-03 DOI: 10.1016/j.rico.2024.100478

Randhir Singh Baghel

In this paper, we have studied the spatiotemporal dynamics of phytoplankton-zooplankton interactions using toxin-producing phytoplankton (TPP) with Holling type II functional responses. Toxin-producing phytoplankton (TPP) diffuses and reduces the grazing pressure on zooplankton. The grazing pressure of zooplankton is lessened by toxin-producing phytoplankton (TPP). The temporal system identifies all equilibrium points. Boundedness and local stability are established under specific parametric conditions. The conditions for the existence of a Hopf-bifurcation at the positive equilibrium by taking the half-saturation constant (

b_{1}

), are also discussed. In a spatial system, we explored Turing instability conditions and patterns with an emphasis on the effect of diffusion variation. Furthermore, we obtained the time evaluation pattern formation of the spatial system. Moreover, the communities of toxin-producing phytoplankton (TPP) are essential to the marine ecosystem because they lessen the mortality of zooplankton caused by grazing pressure. Finally, the basic outcomes are mentioned along with numerical results to provide some support to the analytical findings.

本文利用具有霍林 II 型功能反应的产毒浮游植物（TPP）研究了浮游植物与浮游动物相互作用的时空动态。产毒浮游植物（TPP）会扩散并降低浮游动物的捕食压力。产毒浮游植物（TPP）减轻了浮游动物的捕食压力。时间系统确定了所有平衡点。在特定参数条件下，确定了有界性和局部稳定性。此外，还讨论了通过取半饱和常数 (b1) 在正平衡点存在霍普夫分岔的条件。在空间系统中，我们探讨了图灵不稳定性条件和模式，重点是扩散变化的影响。此外，我们还获得了空间系统模式形成的时间评价。此外，产毒浮游植物（TPP）群落对海洋生态系统至关重要，因为它们能减少浮游动物因放牧压力而死亡。最后，在提到基本结果的同时，还给出了数值结果，为分析结果提供了一些支持。

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引用次数: 0

Linear fractional transportation problem in bipolar fuzzy environment 双极模糊环境中的线性分数运输问题

Q3 Mathematics

Results in Control and Optimization

Pub Date : 2024-10-03 DOI: 10.1016/j.rico.2024.100482

Nilima Akhtar, Sahidul Islam

This article proposes a solution methodology for the Linear Fractional Transportation Problem (LFTP) by incorporating bipolar fuzzy sets (BFSs) to accommodate both positive and negative judgmental perspectives. The approach explores Zimmermann's extension within bipolar fuzzy environment to compare outcomes. In this context, the cost function and constraint coefficients are depicted using interval-valued trapezoidal bipolar fuzzy numbers (IVTrBFNs) and defuzzified by (s, t)-cut. The initial approach employs the simplex method and fuzzy optimization method, renowned for its effectiveness in obtaining optimal solutions. In the alternative method, Bipolar fuzzy programming approach (BFPA) is utilized for better outcome. In this method the LFTP is altered to a Multi-Objective Transportation Problem (MOTP), and BFPA extends Zimmermann's technique under suitable positive and negative membership functions, converting MOTP to a one-objective transportation problem (TP) and solved using LINGO software. Supporting this proposed method some theorems are formulated to demonstrate that the most effective solution of the single-objective TP is a Pareto optimal solution for the corresponding MOTP. A quantitative example is provided for better understanding of the proposed BFPA method alongside two other approaches.

本文提出了一种线性分数运输问题（LFTP）的求解方法，该方法结合了双极模糊集（BFS），以适应积极和消极的判断视角。该方法探索了齐默尔曼在双极模糊环境中的扩展，以比较结果。在这种情况下，成本函数和约束系数使用区间值梯形双极性模糊数（IVTrBFNs）来描述，并通过 (s, t) 切分进行去模糊化。最初的方法采用了单纯形法和模糊优化法，这两种方法在获得最优解方面效果显著。在另一种方法中，为了获得更好的结果，采用了双极模糊编程法（BFPA）。在这种方法中，LFTP 变为多目标运输问题（MOTP），而 BFPA 在适当的正负成员函数下扩展了齐默尔曼技术，将 MOTP 变为单目标运输问题（TP），并使用 LINGO 软件求解。为支持所提出的方法，我们提出了一些定理来证明单目标 TP 的最有效解是相应 MOTP 的帕累托最优解。为了更好地理解所提出的 BFPA 方法和其他两种方法，还提供了一个定量实例。

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引用次数: 0