飞机方案多目标优化的Pareto遗传算法

基于多目标优化问题Pareto最优解的概念 ,提出了一种求解非劣解集的多目标遗传算法 ,重点讨论了算法实现中非劣解集的筛选和适应度的计算 .将该算法应用于假想的干线客机方案优化设计 ,要求巡航段升阻比和有用载荷系数两个目标最大 ,对优化结果进行了分析比较 .研究结果显示出MOGA(Multi ObjectiveGe neticAlgorithms)

多目标线性规划的无目标淹没交互式决策方法(NOSIA)

本文从实用决策角度出发,分析了现有MOLP所存在的目标淹没问题和应用的某些局限性。以凸集理论为基础,提出目标一致性量度矩阵、基准解集和无目标淹没搜索概念,给出求解决策支持矩阵的有效算法。并进一步建立了无目标淹没搜索(NOSS)模型,给出求解MOLP问题的无目标淹没的交互式决策方法(NOSIDM),该方法能够准确方便地反映决策者偏好作用,便于交互作用决策。

基于GA的多约束的多目标排序优化

主要论述了一种解决多约束多目标排序优化的方法。采用在Pareto遗传算法中嵌入优先级约束的检索和调整程序,以保证参与变异和交叉的染色体的有效性。研究结果表明此方法可提高寻优效率。

多目标规划部分弱有效解的求法

多目标规划部分弱有效解的求法魏运财，焉波（吉林电气化高等专科学校，吉林１３２０２１）设ｆｉ（ｘ）是定义在上的实值函数，（ｉ＝１，２，…ｐ，称ｆ（ｘ）＝（ｆ１（ｘ），ｆ２（ｘ），…，ｆｐ（ｘ））为Ｘ上的向量函数，形如下面的数学规划（ＶＰ）称为多目标规划...

基于改进遗传算法的多目标问题的研究

本文讨论了MOGA目前存在的缺陷,并提出利用共享小生境技术为基础更新子群体,并针对遗传迭代过程提出相应的改进遗传策略。策略包括采用了期望、精英保留混合策略以及改进快速自适应的交叉、变异算子。最后,利用改进遗传算法在多目标文献中作实例研究,并取得了良好的应用效果。

一类求解非线性等式和不等式约束优化问题的区间算法

在Moore二分法的基础上,通过构造的区间列L中标志矢量R的分量取值来删除部分不满足约束条件的区域,将非线性约束优化问题转化为初始域子域上的无约束优化问题,该算法可利用极大熵方法求解多目标优化问题,理论分析和数值结果均表明,这种算法是稳定且可靠的.

5R装夹机械臂几何参数优化设计

工作空间是衡量关节式工业机器人工作能力一个重要性能指标,主要由机器人手臂几何参数确定(连杆长度和关节转角范围).将工作空间的截面分为主截面和副截面,给出了主截面的其中一种基本形状.通过分析机械臂手臂连杆长度对工作间所包围长方体能力的影响,给出确定任务路径的最小包容长方体原则.结合装夹机械臂的应用需求,提出一种以材料最省和主截面面积最小为优化目标、以包围目标任务的最小包容长方体为约束的机械臂手臂几何参数的优化方法;采用线性加权法,基于Matlab优化工具箱的约束非线性规划函数命令fmincon,求解机械臂手臂几何参数的多目标非线性规划问题.

一类参数不确定规划的三目标规划解决方法

针对目标函数具有区间参数的不确定优化命题 ,分析了以往不确定优化命题双目标优化满意解的缺陷 ,给出了一种鲁棒优化的定义 ,提出了不确定系统的优化需考虑后悔度 ,把不确定的优化命题转化为确定型的三目标优化命题 .实例分析考虑决策后悔度的三目标优化命题作为不确定优化命题的替代命题更加合理 .该方法的成功作为一个具体实例印证了顾基发研究员“物理 -事理 -人理”的系统方法论的普遍指导意义 .

Optimal path planning method of electric vehicles considering power supply

Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

Multi-objective optimization of rolling schedule based on cost function for tandem cold mill

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.

NSGA Ⅱ based multi-objective homing trajectory planning of parafoil system

Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.

Multiple objectives application approach to waste minimization

Besides economics and controllability, waste minimization has now become an objective in designing chemical processes, and usually leads to high costs of investment and operation. An attempt was made to minimize waste discharged from chemical reaction processes during the design and modification process while the operation conditions were also optimized to meet the requirements of technology and economics. Multiobjectives decision nonlinear programming (NLP) was employed to optimize the operation conditions of a chemical reaction process and reduce waste. A modeling language package-SPEEDUP was used to simulate the process. This paper presents a case study of the benzene production process. The flowsheet factors affecting the economics and waste generation were examined. Constraints were imposed to reduce the number of objectives and carry out optimal calculations easily. After comparisons of all possible solutions, best-compromise approach was applied to meet technological requirements and minimize waste.

An optimization model of UAV route planning for road segment surveillance

Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.

Multi-objective optimization based optimal setting control for industrial double-stream alumina digestion process

The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.

Estimating the Macroeconomic Costs of CO_2 Emission Reduction in China Based on Multi-objective Programming

This paper estimates the macroeconornic costs of CO2 emission reduction in China employing the input-output analysis with the multi-objective programming approach. The results show that the effect of reducing CO2 emissions on China＇s economy is significant. Under the present conditions, the estimated macroeconomic costs of CO2 emission reduction in 2010 for China are approximately 3,100-4,024 RMB t-1. The stronger the abatement actions, the higher the macroeconomic costs of per unit emission reduction would be. Excavation industry, oil industry, chemical industry, and metal smelting industry have high potential to abate their CO2 emissions.

Model of Optimal Forest Management Unit Area for a Sustainable Forest Resource Administration

Deforestation is one of the most crucial problems in Indonesia. It creates a number of environmental problems, e.g., landslides, loss of biological diversity, and decrease of carbon sequestration which are impacting human lives, There are a number of underlying causes, often stemmed from the emphasis on a particular forest management objective. Despite numerous forest policies and regulations established by the government, deforestation continues to happen. Quite often, the policies and regulations remain ＂paper tiger＂, which means ineffectual on the ground. One of the contributing factors to deforestation is the lack of custodian for the management of the forests. The regulation, such as law No. 41/1999, stipulates that all state forests must be managed under a FMI3 （forest management unit） as the custodians. The objective of this research is to develop an optimal model for FMU. Using the LGP （linear goal programming）, this research attempts to develop an optimum model for conservation areas. It assumes that the existing zoning approach implemented by the government in conservation areas is inappropriate. The optimum zoning model is expected to improve forest management and restore the forest function as a life supporting system and biological diversity conservation.

Multi-objective optimization of space station short-term mission planning

This paper studies the multi-objective optimization of space station short-term mission planning(STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocate the execution time effectively, schedule the on-board astronauts properly, and arrange the devices reasonably. The STMP concept models for problem definitions and descriptions are presented, and then an STMP multi-objective planning model is developed. To optimize the STMP problem, a Non-dominated Sorting Genetic Algorithm II(NSGA-II) is adopted and then improved by incorporating an iterative conflict-repair strategy based on domain knowledge. The proposed approach is demonstrated by using a test case with thirty-five missions, eighteen devices and three astronauts. The results show that the established STMP model is effective, and the improved NSGA-II can successfully obtain the multi-objective optimal plans satisfying all constraints considered. Moreover, through contrast tests on solving the STMP problem, the NSGA-II shows a very competitive performance with respect to the Strength Pareto Evolutionary Algorithm II(SPEA-II) and the Multi-objective Particle Swarm Optimization(MOPSO).

Optimal Land Use Structure for Sustainable Agricultural Development——A Case Study in Changsha County,South Central China

Environmental and social problems caused by overfertilization,excessive pesticides,and encroachment on farmland are increasingly serious in agricultural settings,especially in suburban agricultural areas and highly intensive agricultural areas.Hence,modern agriculture not only pursues economic benefits,but it also pays more attention to ecological functions and social stability.This paper proposes a set of methods which are designed to realize optimal agricultural benefits and sustainable development by scientifically adjusting the land use structure.Taking Changsha County in South Central China as a case study,this paper first built an index system and adopted the information entropy-TOPSIS method to assess the economic,social,and ecological benefits of agricultural land use.Next,a coupled coordination model and an obstacle model were chosen to diagnose those factors that remained as obstacles to achieving the sustainable and coordinated development of the benefits of agricultural land use.Finally,based on the analysis of the changes in the benefits and obstacles over time,socio-economic and ecological constraints were established,and the multi-objective linear programming method(MOLP)was used to determine the comprehensive benefits and optimal land use structure.The results indicate that:(1)The agricultural benefits were stably increasing from 0.20 in 1996 to 0.79 in 2016.(2)The economic benefit index is no longer the main obstacle,while the social benefit index,which includes components such as the food security index,has become the principal influencing factor.(3)The optimal land use structure and comprehensive benefits were presented by taking into consideration the economic development,environmental protection,and social needs.This study emphasizes economic development,but it also seeks coordinated development with comprehensive benefits.The results of the study could provide scientific recommendations for optimizing the agricultural land use spatial patterns and sustainable land use.