Differential Evolution Algorithm Based on Ensemble of Constraint Handling Techniques and Multi-Population Framework

Aimed at improving the insufficient search ability of constraint differential evolution with single constraint handling technique when solving complex optimization problem, this paper proposes a constraint differential evolution algorithm?based on ensemble of constraint handling techniques and multi-population?framework, called ECMPDE. First, handling three improved variants of differential evolution algorithms are dynamically matched with two constraint handling techniques through the constraint allocation mechanism. Each combination includes three variants with corresponding constraint handling technique?and these combinations are in the set. Second, the population is divided into three smaller subpopulations and one larger reward subpopulation. Then a combination with three constraint algorithms is randomly selected from the set, and the three constraint algorithms are run in three sub-populations respectively. According to the improvement of fitness value, the optimal constraint?algorithm is selected to run on the reward sub-population, which can share?information and close cooperation among populations. In order to verify the effectiveness of the proposed algorithm, 12 standard constraint optimization problems?and 10 engineering constraint optimization problems are tested. The experimental results show that ECMPDE is an effective algorithm for solving constraint optimization problems.

Feasibility-Guided Constraint-Handling Techniques for Engineering Optimization Problems

The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm and requires constraint handling techniques(CHTs)to solve constrained optimization problems(COPs).For this purpose,we integrate two CHTs,the superiority of feasibility(SF)and the violation constraint-handling(VCH),with a PSO.These CHTs distinguish feasible solutions from infeasible ones.Moreover,in SF,the selection of infeasible solutions is based on their degree of constraint violations,whereas in VCH,the number of constraint violations by an infeasible solution is of more importance.Therefore,a PSO is adapted for constrained optimization,yielding two constrained variants,denoted SF-PSO and VCH-PSO.Both SF-PSO and VCH-PSO are evaluated with respect to ve engineering problems:the Himmelblau’s nonlinear optimization,the welded beam design,the spring design,the pressure vessel design,and the three-bar truss design.The simulation results show that both algorithms are consistent in terms of their solutions to these problems,including their different available versions.Comparison of the SF-PSO and the VCHPSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used.We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants.

Economical Requirements Elicitation Techniques During COVID-19: A Systematic Literature Review

Requirements elicitation is a fundamental phase of software development in which an analyst discovers the needs of different stakeholders and transforms them into requirements.This phase is cost-and time-intensive,and a project may fail if there are excessive costs and schedule overruns.COVID-19 has affected the software industry by reducing interactions between developers and customers.Such a lack of interaction is a key reason for the failure of software projects.Projects can also fail when customers do not know precisely what they want.Furthermore,selecting the unsuitable elicitation technique can also cause project failure.The present study,therefore,aimed to identify which requirements elicitation technique is the most cost-effective for large-scale projects when time to market is a critical issue or when the customer is not available.To that end,we conducted a systematic literature review on requirements elicitation techniques.Most primary studies identified introspection as the best technique,followed by survey and brainstorming.This finding suggests that introspection should be the first choice of elicitation technique,especially when the customer is not available or the project has strict time and cost constraints.Moreover,introspection should also be used as the starting point in the elicitation process of a large-scale project,and all known requirements should be elicited using this technique.

Variations in Stable Carbon Isotopic Composition of n-Alkanes from Ordovician- and Triassic-Derived Oils in Lunnan Oilfield, Tarim Basin, NW China: Global Paleoenvironmental Constraints

Molecular stable carbon isotope technique was employed to study well-sourced crude oils collected from a single drilling well and from the entire Lunnan oilfield, Tarim Basin, NW China. The stable carbon isotopic composition of n-alkanes from crude oils showed that Ordovician-derived oils are enriched in {}+{13}C and Triassic-derived oils are depleted in {}+{13}C. This is consistent with the distribution and evolution trend of stable carbon isotope ratios in crude oils/organic matter from all over the world in geological history (Stahl, 1977; Andrusevich et al., 1998). An extensive survey of literature indicates that, except for thermal maturity, organic matter input and depositional environment, paleoenvironmental background is another key factor that affects the stable carbon isotopic composition of Ordovician- and Triassic-derived crude oils. The results showed that gas chromatographic-isotope ratio mass spectrometry (GC-C-IRMS), combining with biogeochemical evolution of organic matter in geological history, may be a powerful tool in refining oil/oil, oil/source correlations in multi-age, multi-source petroliferous basins like Tarim.

Superlinear Convergence of a Smooth Approximation Method for Mathematical Programs with Nonlinear Complementarity Constraints

Mathematical programs with complementarity constraints(MPCC) is an important subclass of MPEC.It is a natural way to solve MPCC by constructing a suitable approximation of the primal problem.In this paper,we propose a new smoothing method for MPCC by using the aggregation technique.A new SQP algorithm for solving the MPCC problem is presented.At each iteration,the master direction is computed by solving a quadratic program,and the revised direction for avoiding the Maratos effect is generated by an explicit formula.As the non-degeneracy condition holds and the smoothing parameter tends to zero,the proposed SQP algorithm converges globally to an S-stationary point of the MPEC problem,its convergence rate is superlinear.Some preliminary numerical results are reported.

An Intelligent Approach in Design Optimzation Based on Determining Constraints Compatibility

Based on monotonicity analysis and computer symbolic manipulating technique,a procedure for determining constraints compatibility in design optimization hasbeen proposed in this paper. By using the proposed method relationshipsbetween constrains can be determined and the optimization is greatly simplifid.The method is code with intelligent production systems.

A Class of Algorithms for Solving LP Problems by Prioritizing the Constraints

Linear programming is a method for solving linear optimization problems with constraints, widely met in real-world applications. In the vast majority of these applications, the number of constraints is significantly larger than the number of variables. Since the crucial subject of these problems is to detect the constraints that will be verified as equality in an optimal solution, there are methods for investigating such constraints to accelerate the whole process. In this paper, a technique named proximity technique is addressed, which under a proposed theoretical framework gives an ascending order to the constraints in such a way that those with low ranking are characterized of high priority to be binding. Under this framework, two new Linear programming optimization algorithms are introduced, based on a proposed Utility matrix and a utility vector accordingly. For testing the addressed algorithms firstly a generator of 10,000 random linear programming problems of dimension n with m constraints, where , is introduced in order to simulate as many as possible real-world problems, and secondly, real-life linear programming examples from the NETLIB repository are tested. A discussion of the numerical results is given. Furthermore, already known methods for solving linear programming problems are suggested to be fitted under the proposed framework.

基于多目标进化的超限超重货物运输专列路径优化方法

针对超限超重货物运输专列路径优化问题,引入限界改造和桥梁加固要素,以铁路运能损失、运输时间和运输费用的最小化为优化目标,构建铁路超限超重货物运输专列路径优化模型;考虑专列同时运送多件超限超重货物的特点,设计货物综合投影算法,并以Pareto支配关系框架下的NSGA-Ⅱ多目标进化算法为基础,结合基于移动不可行解的自适应惩罚函数的约束处理技术及超限超重货物运输专列开行特征,提出一种基于多目标进化的铁路超限超重货物运输专列路径优化算法。实例分析结果表明:该方法能高效合理地处理路径优化任务中的多个目标;与常用的3种约束多目标算法相比,设计的优化算法能使计算耗时降低0.24%~29.94%、超体积指标值提高4.25%~13.11%,并得到一组收敛性和多样性更好的相对最优方案。该方法克服了传统专列路径优化中单纯依靠经验或从备选方案中择优的弊端,可为铁路超限超重货物运输专列路径决策提供技术支持。

高温测量降本增效实践与研究

旨在研究高温测量过程降本增效的关键策略:聚焦加热炉测温优化、热偶使用管理降本方法、计量过程数据高效处理。在探究这些策略的过程中,炉顶穿孔引导测温方法、热偶维修技术以及帆软数据分析展示模块成为实现高温测量过程降本增效目标的重要手段。穿孔引导测温方法操作便捷,不仅提升了测温效率,还提升了测温过程的稳定性和准确性。同时,针对热电偶使用,开发出了热电偶维修裁剪工艺,增加了热电偶循环利用率,减少了热电偶使用成本。在数据处理方面,帆软数据报表模块的应用彰显了其在实现计量过程数据高效处理上的优势。通过该平台,生产数据可以更为直观、清晰地呈现,同时也提供了对数据进行深入分析的功能。通过实际生产案例的验证,这些优化措施显著提高了生产效率、降低了成本。更重要的是,这些策略的实施对于冶金行业的可持续发展和提升竞争力具有重要意义。

汉服传统古法裁剪的规律研究

近年来,汉服文化的复兴浪潮席卷全国,越来越多的人开始关注并热爱这种传统服饰。汉服作为中华民族的文化瑰宝,有着深厚的历史底蕴,展现了古代工匠的卓越智慧和精湛技艺。然而,目前对汉服传统古法裁剪的深入研究还远远不够,许多制作细节和规律尚未得到充分的发掘和整理。因此,文章旨在系统探究汉服传统古法裁剪的基本规律及其细节处理,以期更深入地挖掘汉服裁剪技艺的文化内涵与美学价值,并为现代汉服的设计与制作提供坚实的理论基础和实践指导。

钢箱拱桥斜拉扣挂施工法拆索工序研究

斜拉扣挂体系钢箱拱桥拱肋合龙后需进行拆索工作,拆索时桥梁各构件均会产生应力变化从而影响结构安全性。为探究钢箱拱桥合理的拆索顺序及拆索时可能出现的极限不对称状态,以车田江大桥为实际工程背景,建立有限元模型,分别模拟四种拆索方案对拱肋应力及位移的影响。发现当从拱顶向拱脚依次拆索时,扣索索力的增幅最小;相反,若从拱脚向拱顶依次拆索,则会导致拱肋的竖向位移和应力极值达到最大。因此,从拱顶向拱脚依次拆索的方案最符合实际施工需求。采用Midas/Civil软件对几种极限不对称拆索状态进行模拟,结果表明:扣索、背索的拆除应尽量同步进行,以确保结构稳定。同时,两岸的拆索进度差异以及左右两幅的拆索进度差异都应控制在1束索以内,以减小对桥梁结构的不利影响。

基于双阶段搜索的约束进化多任务优化算法

高效地平衡算法的多样性、收敛性和可行性是求解约束多目标优化问题(CMOP)的关键;然而,复杂约束的出现给该类问题的求解带来了更大的挑战。因此,提出一种基于双阶段搜索的约束进化多任务优化算法(TEMA),通过完成两个协同进化的任务实现多样性、收敛性和可行性之间的平衡。首先,进化过程由探索和利用两个阶段组成,分别致力于加强算法在目标空间的广泛探索能力和高效搜索能力;其次,设计一种动态约束处理策略以平衡种群中可行解的比例,从而增强算法在可行区域的探索能力;再次,提出一种回退搜索策略,利用无约束Pareto前沿所包含的信息指导算法向约束Pareto前沿快速收敛;最后,在两个基准测试集中的23个问题上进行对比实验。实验结果表明,TEMA分别在14个和13个测试问题上取得最优反世代距离(IGD)值和超体积(HV)值,体现出明显优势。

求解复杂约束优化问题的集成多策略差分进化算法

工程和科学领域中的优化问题常常具有大量的约束限制,称为约束优化问题.这类问题要求算法有能力在可行域中寻找问题的最优解.本文针对约束优化问题提出一种集成多策略的差分进化算法(Differential Evolution with Ensemble Multi-Strategies,EMSDE).首先,提出一种用于约束优化的参数自适应策略,利用归一化罚函数作为权重引导参数自适应地生成.其次,结合约束和动态罚函数法设计一种新的约束处理技术.最后,采用CEC2017约束优化基准函数来测试EMSDE和7种经典的约束优化算法.实验结果表明,相比7种经典的算法,EMSDE算法具有很强的竞争力.

TGQ-200RC型多工艺自动化钻机的研制与应用

新一轮找矿突破战略行动对钻探技术提出更高要求,利用浅钻技术在浅覆盖区进行快速查证是重要的技术手段。多工艺钻探可以为复杂地层钻探施工提供绿色高效的钻探技术支撑。围绕这一需求研制了TGQ-200RC型多工艺自动化钻机,制定了钻机的总体方案,研制了多工艺动力头、夹持拧卸装置、6自由度移摆管机构、车装集成式液压储杆库、电液控制及参数监测系统等钻机主要部件,规划了自动加减钻杆过程中多机构协同动作控制流程。实钻试验表明,TGQ-200RC型钻机钻进效率高,取样质量好,具有多工艺、机动化、自动化、数字化等特点,单次自动加减钻杆平均用时约90 s,配合无线遥控可实现孔口无人操作,有效降低劳动强度,提高施工安全性。TGQ-200RC型多工艺自动化钻机可以为构建绿色、高效、经济的快速查证钻探技术体系提供坚实支撑,为推动国内浅层钻探装备自动化升级提供有益借鉴。

基于激光净空雷达数据的叶片信号提取

为了降低雾天风力发电机组叶片信号的虚警率,以激光净空雷达获取的原始信号数据为基础数据源,在信号预处理的基础上,采用时空约束的方法,实现了叶片信号的准确提取;并将集成了该叶片信号提取方法的激光净空雷达在常年有雾的地区进行了挂机试验。结果表明,所提出的叶片信号提取方法取得了较好的效果,叶片虚警率低于2%,提升了激光净空雷达测距数据的可靠性和环境适应性。该研究为激光净空雷达用于风机净空监测提供了参考。

基于多策略融合和约束处理技术的差分进化算法

当约束优化问题的目标函数结构比较复杂,约束条件较为严格时,差分进化算法(Differential Evolution,DE)的收敛性能表现较差。为发挥基于群智能搜索算法的优势,本文提出了一个基于等级划分、状态转移和不可行解处理的多策略融合差分进化算法(Multi-Strategy fusion Differential Evolution,MSDE)。首先,根据目标函数值和约束违反度值对父代群体进行等级划分,并根据等级特征将子群体划分为3个层次;然后,利用不同等级和层次的特征设计有效的进化操作,提高差分进化算法的勘探和挖掘能力;进一步,根据不可行解的分布特征将群体进行状态转移,使转移后的个体在决策空间具有较好的分布;接着,利用转移后个体的分布特征设计了约束处理技术,提高个体向可行域收敛的概率,使不可行解以较高的概率转移到可行域中;最后,与4个最新的进化算法做了仿真实验,结果表明,本文提出的相关策略改进了DE算法的性能。

求解一类线性等式约束凸优化问题的加速方法

具有线性约束的凸优化问题是数学规划中的一类经典问题。本文将借助对偶理论,研究求解一类具有线性等式约束的凸优化问题的加速算法。由于此类问题的对偶问题是一个具有两块可分离结构的凸优化问题,我们基于Goldstein等人在加速交替方向乘子法方面的重要工作,提出了一种在弱化条件下求解线性等式约束凸优化问题的加速方法。我们的方法与Goldstein等人的加速交替方向乘子法的不同之处为:1)目标函数仅要求具有凸性(而不必强凸);2)罚参数仅要求β>0(而不受目标函数的利普希茨常数、强单调系数的限制)。基于上述弱化的条件,我们证明了所提的加速交替方向乘子法依然具有收敛性和O(1/k^(2))的收敛率。我们将条件弱化后的加速交替方向乘子法用于求解一个图像重建问题。数值实验结果表明,条件弱化后的加速交替方向乘子法依然具有较好的数值效果。

A NEW CONSTRAINTS IDENTIFICATION TECHNIQUE-BASED QP-FREE ALGORITHM FOR THE SOLUTION OF INEQUALITY CONSTRAINED MINIMIZATION PROBLEMS

In this paper, we propose a feasible QP-free method for solving nonlinear inequality constrained optimization problems. A new working set is proposed to estimate the active set. Specially, to determine the working set, the new method makes use of the multiplier information from the previous iteration, eliminating the need to compute a multiplier function. At each iteration, two or three reduced symmetric systems of linear equations with a common coefficient matrix involving only constraints in the working set are solved, and when the iterate is sufficiently close to a KKT point, only two of them are involved. Moreover, the new algorithm is proved to be globally convergent to a KKT point under mild conditions. Without assuming the strict complementarity, the convergence rate is superlinear under a condition weaker than the strong second-order sufficiency condition. Numerical experiments illustrate the efficiency of the algorithm.

QFT preflter design for multivariable systems using interval constraint satisfaction technique

In this paper, a computationally efficient method is proposed for automated design of the prefilters for multivariable systems. In quantitative feedback theory （QFT） method, proposed by Horowitz, the prefilter is designed to achieve the desired tracking specifications. In the proposed approach, we pose the prefilter design problem as an interval constraint satisfaction problem and solve it using the well-established interval constraint satisfaction techniques. The proposed method finds optimal values of the parameters of fixed structure prefilter within the initial search domain. An approach based on prefilter synthesis for single-input single-output is already developed. The purpose of this paper is to extend this approach to QFT prefilter design for general multivariable systems. To validate the above design approach, we applied the method to a laboratory setup of magnetic levitation system.

基于模糊滑模控制的双6-DOF机械臂协同控制方法

目前,双机械臂搬运系统的传统搬运策略存在搬运效果差、双机械臂同步性较差等问题,同时双机械臂的轨迹规划只针对末端轨迹,并未考虑运动状态下机械臂关节处产生的力矩。通过建立UR5机械臂的模型,分析双机械臂搬运状态的运动特点,建立了一种新的基于模糊滑模控制的双机械臂协同控制方法。首先通过对双机械臂建立运动学闭链约束关系,使得双机械臂能够实现期望轨迹运动,其次建立双机械臂的相邻误差交叉耦合同步策略,意在解决双机械臂之间的同步性问题,最后提出的模糊滑模控制策略,通过建立滑模面和滑模趋近律,实现机械臂的轨迹跟踪效果与关节处的控制输入稳定。最后通过对UR5机械臂进行滑模控制仿真,验证了该策略的可行性。