Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment

This study presented a multi-objective linear fractional inventory (LFI) problem with generalised intuitionistic fuzzy numbers. In modelling, the authors have assumed the ambiances where generalised trapezoidal intuitionistic fuzzy numbers (GTIFNs) used to handle the uncertain information in the data. Then, the given multi-objective generalised intuitionistic fuzzy LFI model was transformed into its equivalent deterministic linear fractional programming problem by employing the possibility and necessity measures. Finally, the applicability of the model is demonstrated with a numerical example and the sensitivity analysis under several parameters is investigated to explore the study.

Sustainable Multi-Objective Multi-Reservoir Optimization Considering Environmental Flow

Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.

Optimal design of modular dual-field modulated permanent magnet linear motors with thrust characteristics

To reduce thrust ripple and cost and improve the average thrust of permanent magnet linear motors,a modular dual-field modulation permanent magnet linear motor was studied,and the parameters were optimized.First,sensitive parameters were selected using the Taguchi method,and then the optimal variables were sampled using the optimal Latin hypercube experimental design method and an ensemble of surrogates model of optimization objectives,and its accuracy was verified.Next,a multi-objective particle swarm optimization algorithm was used to optimize the purpose of“maximum average thrust and minimum thrust ripple”,and the Pareto front of average thrust and thrust ripple was obtained.Finite element analysis showed that the optimized modular dual flux-modulation permanent magnet linear motor(MDFMPMLM)had a 29.5%reduction in thrust ripple and a 5%increase in average thrust compared to the original motor.This study provided an effective method for improving the performance of permanent magnet linear motors.

Fuzzy Optimal Control Design for Ship Steering

This paper presents a method to design a control scheme for nonlinear systems using fuzzy optimal control.In the design process,the nonlinear system is first converted into local subsystems using sector non linearity approach of Takagi Sugeno(T S)fuzzy modeling.For each local subsystem,an optimal control is designed.Then,the parameters of local controllers are defuzzified to construct a global optimal controller.To prove the effectiveness of this control scheme,simulations are performed using the mathematical model of Esso Osaka tanker ship for set point regulation with and without disturbance and reference tracking.In addition,the simulation results are compared with that of a PID controller for further verification and validation.It has been shown that the proposed optimal controller can be used for the nonlinear ship steering with good rise time,zero steady state error and fast settling time.

Multi-objective Model Predictive Control of Grid-connected Three-level Inverter Based on Hierarchical Optimization

In order to solve the problem of weighting factors selection in the conventional finite-control-set model predictive control for a grid-connected three-level inverter,an improved multi-objective model predictive control without weighting factors based on hierarchical optimization is proposed.Four control objectives are considered in this strategy.The grid current and neutral-point voltage of the DC-link are taken as the objectives in the first optimization hierarchy,and by using fuzzy satisfaction decision,several feasible candidates of voltage vectors are determined.Then,the average switching frequency and common-mode voltage are optimized in the second hierarchy.The average ranking criterion is introduced to sort the objective functions,and the best voltage vector is obtained to realize the coordinated control of multiple objectives.At last,the effectiveness of the proposed strategy is verified by simulation results.

Evaluation and advancement of the integrated circular economy model of farming and stock raising

The integrated circular economy model of farming and stock raising(ICEMFSR)has attracted increased attention as an effective model for solving the current irrational allocation of agricultural resources and realizing the agricultural value-added industrial chain.This study uses emergy analysis to comprehensively examine and evaluate the economic benefits,environmental pressures,and sustainable development levels of ICEMFSR in Shucheng County,China.The results show that the ICEMFSR possesses the value of popularization with optimally allocated resources in the studied region,in which the emergy yield ratio(EYR),emergy loading ratio(ELR),and emergy sustainable index(ESI)in this model accounted for 3.59,1.25,and 2.89,respectively.This result indicates a leading position in the national agricultural system.Hence,this study constructs a new model based on the coupling of emergy evaluation and multi-objective linear programming to study ICEMFSR.Consequently,the EYR,ELR,and ESI respectively varied by +24.23%,10.40%,and +38.06%after replanning of ICEMFSR.This variation implies a significant improvement in the sustainable development level of the model.In addition,the optimized scenario design for key substances is proposed based on traceability and the reduce-reuse-recycle principle,including biogasification of crop straw and enhancement of crop scientific planting capacity.

The Impact on the Environment and Economy Due to the Introduction of Electric Cars: Based on the Fuzzy Synthetical Evaluation Method

In this paper, we establish a model to analyze the influence of widespread use of electric vehicle on environment, society and economist based on Fuzzy Comprehensive Evaluation method. We set the fuzzy objects are internal combustion engine vehicles, pure electric vehicles and hybrid electric vehicles. Considering the difference of environment, society and economics, we use of three different kinds to define the fuzzy evaluation factor sets. According to the data and calculating results, we finally obtain fuzzy synthetical evaluation matrix. Through comparing and analysis, we draw such conclusion that the widespread using of electric vehicle is benefit for both environment and economics, while has disadvantageous influence for some aspects on society. In Section 3, we establish a model to estimate the influence of widespread use of electric vehicles on energy saving. According to the proportion of coal resources in the whole energies, we use Linear Regression Model to forecast the development situation in the following several years. Contrasting energy consumptions of electric vehicles and internal combustion engine vehicles, we calculate the whole energies saved by widespread use of electric vehicles. In Section 4, we establish a multi-objective programming model to plan the number and type of power station. Considering the thermal power, hydropower, nuclear power and solar power as four ways, combined with the funds of setting up power station, running funds and the cost of dealing with the pollutants, we find the objective function and four constraints, and finally we reach optimal solution using lingo software.

Analytic design of information granulation-based fuzzy radial basis function neural networks with the aid of multiobjective particle swarm optimization

Purpose–The purpose of this paper is to consider the concept of Fuzzy Radial Basis Function Neural Networks with Information Granulation(IG-FRBFNN)and their optimization realized by means of the Multiobjective Particle Swarm Optimization(MOPSO).Design/methodology/approach–In fuzzy modeling,complexity,interpretability(or simplicity)as well as accuracy of the obtained model are essential design criteria.Since the performance of the IG-RBFNN model is directly affected by some parameters,such as the fuzzification coefficient used in the FCM,the number of rules and the orders of the polynomials in the consequent parts of the rules,the authors carry out both structural as well as parametric optimization of the network.A multi-objective Particle Swarm Optimization using Crowding Distance(MOPSO-CD)as well as O/WLS learning-based optimization are exploited to carry out the structural and parametric optimization of the model,respectively,while the optimization is of multiobjective character as it is aimed at the simultaneous minimization of complexity and maximization of accuracy.Findings–The performance of the proposed model is illustrated with the aid of three examples.The proposed optimization method leads to an accurate and highly interpretable fuzzy model.Originality/value–A MOPSO-CD as well as O/WLS learning-based optimization are exploited,respectively,to carry out the structural and parametric optimization of the model.As a result,the proposed methodology is interesting for designing an accurate and highly interpretable fuzzy model.

基于多目标模糊优化模型的兰州市水资源优化配置研究

构建可持续发展视角下的兰州市水资源优化配置模型。以净效益系数、水利用系数和供水成本为指标,运用熵值法修正由层次法获得的各项指标的权重,并采用多目标模糊线性优化模型确定各用水部门的综合效益系数,代入线性规划法求解规划年2020年在不同用水保证率(多年平均、50%、75%、90%)下各用水部门分配水量。分配结果(多年平均)与预测结果相比工业用水量减少了1.363 5亿m^3,农业用水量和生态用水量分别增加了1.126 0和0.237 5亿m^3,该分配结果有利于实现兰州区域经济的可持续发展与水生态的协调发展。

GA矩阵编码方法及其在模糊建模中的应用

在遗传算法 (GA)的实际应用中 ,许多问题都可以采用树结构描述 .模糊建模中的结构辨识是指如何划分输入空间 ,它是一种复杂的非线性优化过程 ,模糊树模型可将输入空间的划分表示成二叉树结构的形式 .本文提出了一种树结构的矩阵编码方法 ,这种编码方法直观、简单 ,非常适合遗传算法的各种遗传操作 .针对模糊树模型 ,以树结构为个体 ,采用矩阵编码方式 ,利用遗传算法优化输入空间的划分 。

软计算求解分布式多工厂多顾客的供应链准时化生产计划问题

描述了分布式多工厂、多顾客的供应链准时化生产计划问题 ,以实现最小化提前 /拖期惩罚费用、生产成本、产品运输费用之和为目标建立了数学模型 ,将遗传算法与模糊逻辑相结合 ,设计了软计算方法求解模型 ,采用基于规则方法的模糊规则量化方法求解模糊决策 ,并将模糊决策嵌入遗传算法 ,使得算法具有比分枝定界法更快的寻优能力和更广的适应范围。

基于模糊线性规划的土地整理优化研究

分析研究了模糊线性规划及其对土地整理项目规划的适用性 ,并结合湖北省秭归县土地整理项目实例 ,对模糊线性规划在土地整理项目规划中的应用进行了系统的分析和研究 ,摸索了一套土地整理优化的方法体系 。

基于不确定性优化模型的空气质量管理

针对空气质量管理系统存在的多重不确定性与复杂性,基于区间线性规划(ILP)、随机数学规划(SMP)和模糊可能性规划(FPP)方法,研究开发了区间随机模糊可能性规划(ISFPP)模型以实现有效管理政策的制订。开发的ISFPP模型不仅能够处理多重不确定性,而且能够反映系统复杂性。同时,ISFPP模型能够分析不同置信水平下的管理情景。将ISFPP模型应用到一个假设的空气质量管理案例中,结果表明,置信水平的变化,可能导致系统总成本、污染物处理量及超标排放量发生相应的变化;在不同的置信水平下,生产企业能够选择合适的污染物控制措施,确定合理的污染物处理量和超标排放量。因而,模型结果能够用于生成决策方案,进而帮助决策者制订有效的管理政策。

基于FANP的私用飞行驾驶员安全驾驶行为评价模型

为了正确评价私用飞行员的安全驾驶行为,在系统分析飞行运行全过程的基础上,建立了基于模糊网络分析法(FANP)的私用驾驶员安全驾驶行为评价模型.针对模型中三角模糊数互补判断矩阵一致性检验过于复杂的问题,引入了最小方差的非线性规划模型,通过求取最优解以简化计算,获得可信度较高的评价指标权重.以某航校飞行学员的评价为实例进行实证分析,结果表明,该模型较传统评价方式更全面、客观,有助于飞行员的安全驾驶行为训练.

重大灾害后应急物资调配模糊优化研究

在总结国内外学者研究的基础上,分析了灾后应急物资调配的特点及和普通物资调配的区别,建立以运输时间最短为主要目标,以运输成本最小为第二目标,需求量、运输量以及运输能力为约束条件的多目标模糊线性规划模型,并利用模糊数排序指标模型简化并求解。最后以汶川地震中3个受灾乡镇应急物资调配为例进行实证分析,对灾后应急物资调配策略及模型进行了验证,并对调配效果进行了分析。

多目标投资组合模型的模糊两阶段解法

对多目标证券组合投资模型进行了研究,模型以绝对偏差和代替方差作为投资组合的风险度量.该模型是一个多目标线性优化问题,采用两阶段模糊算法对模型进行求解,最后给出了该模型的一个实例的最优解.

模糊系统理论的工业应用──(Ⅲ)工业过程的模糊调优技术

本文是《模糊系统理论的工业应用》专题系列的最后一部分，介绍模糊逻辑应用于工业调优的理论进展和具体技术，并简单介绍对造纸制浆过程质量控制和操作优化的一个应用实例。

多指标综合评价的一种灰色模糊决策方法

针对多指标综合评价的实际问题,综合运用灰色理论和模糊数学理论,提出了一种新的定性与定量相结合的灰色模糊决策方法,并给出了相关参数的确定方法.特别地,文中在确定评价指标的权重时,在传统的层次分析法基础上进行改进提出了一种新方法——带有专家可信度的非线性优化层次分析法.

基于T-S模糊模型的转台鲁棒最优控制器设计

针对飞行器仿真转台系统的非线性以及不确定性问题,提出了基于T-S模糊模型的鲁棒最优控制器设计方法。首先,利用IF-THEN模糊规则将转台速度环系统的状态空间分成不同的区域,构建具有参数不确定性的T-S模糊模型;然后,根据给定的最优性能指标要求以及控制输入约束,通过求解一组线性矩阵不等式(LMIs)进行鲁棒最优控制器设计。仿真结果表明,该方法不仅具有比较好的控制效果,而且能有效地解决控制输入约束问题,并能很好地保证对参数变化的鲁棒稳定性。

基于T-S模型的约束鲁棒保性能飞行控制律设计

对一类具有范数有界参数不确定Takagi-Sugeno(T-S)模糊模型系统,采用状态反馈并行分配补偿结构,综合考虑变量约束和多个性能指标,研究了约束鲁棒最优保性能飞行控制律设计问题。改进输入、输出及状态约束线性矩阵不等式,提出了带约束模糊最优保性能控制定理。在一般抗干扰控制基础上引入不确定性矩阵,证明了模糊鲁棒最优抗干扰定理。综合上述结论,推导出带约束模糊最优保性能抗干扰定理。最后,建立了飞机不确定T-S模糊模型,分别设计了满足上述3个定理的飞行控制律,并进行了仿真与对比分析,结果验证了该设计方法的有效性。