A Bi-population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium-scale Expensive Problems

This study presents an autoencoder-embedded optimization(AEO)algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems(MEPs).A huge search space can be compressed to an informative lowdimensional space by using an autoencoder as a dimension reduction tool.The search operation conducted in this low space facilitates the population with fast convergence towards the optima.To strike the balance between exploration and exploitation during optimization,two phases of a tailored teaching-learning-based optimization(TTLBO)are adopted to coevolve solutions in a distributed fashion,wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary process.Also,a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence speed.The proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to 200.As indicated in our experiments,TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base optimizer.Compared with the state-of-the-art algorithms for MEPs,AEO shows extraordinarily high efficiency for these challenging problems,t hus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization.

Evolutionary Algorithm with Ensemble Classifier Surrogate Model for Expensive Multiobjective Optimization

For many real-world multiobjective optimization problems,the evaluations of the objective functions are computationally expensive.Such problems are usually called expensive multiobjective optimization problems(EMOPs).One type of feasible approaches for EMOPs is to introduce the computationally efficient surrogates for reducing the number of function evaluations.Inspired from ensemble learning,this paper proposes a multiobjective evolutionary algorithm with an ensemble classifier(MOEA-EC)for EMOPs.More specifically,multiple decision tree models are used as an ensemble classifier for the pre-selection,which is be more helpful for further reducing the function evaluations of the solutions than using single inaccurate model.The extensive experimental studies have been conducted to verify the efficiency of MOEA-EC by comparing it with several advanced multiobjective expensive optimization algorithms.The experimental results show that MOEA-EC outperforms the compared algorithms.

costly、dear和expensive的异同

costly、dear 和 expensive 是一组英文中颇为常见的形容词,汉语都译成“昂贵的”。然而,它们在意义上、用法上又各有不同,稍不留意就会出现误会,现分述如下:1.costly:昂贵的、价值高的(含有豪华、珍贵、精致等意味)。指“

Low-cost clothing outlasts expensive pieces

If you’ve been shelling out for designer clothing in the hopes that it will be more durable than cheaper options, you might want to reconsider it. A new study from The University of Leeds suggests that low-cost clothing might actually outlast pricier pieces.

不动声色 流露尊贵——Express expensiveness smoothly

生活在被重视的空间里是很惬意的,对男人尤其如此。 生活在被忽略的氛围中是一件不可容忍的事,对男人尤其如此。 这样一来,问题就出现了。 第一是差额的问题:所有人都希望自己被看重,所有人都在规避被忽视的窘境。而任何时候,在喧闹的人群中,众人的目光从来不会过于分散,被瞩目的名额永远是有限的。不管那些对着焦点翘首张望的人们心里。

Surrogate-assisted differential evolution using manifold learning-based sampling for highdimensional expensive constrained optimization problems

To address the challenges of high-dimensional constrained optimization problems with expensive simulation models,a Surrogate-Assisted Differential Evolution using Manifold Learning-based Sampling(SADE-MLS)is proposed.In SADE-MLS,differential evolution operators are executed to generate numerous high-dimensional candidate points.To alleviate the curse of dimensionality,a Manifold Learning-based Sampling(MLS)mechanism is developed to explore the high-dimensional design space effectively.In MLS,the intrinsic dimensionality of the candidate points is determined by a maximum likelihood estimator.Then,the candidate points are mapped into a low-dimensional space using the dimensionality reduction technique,which can avoid significant information loss during dimensionality reduction.Thus,Kriging surrogates are constructed in the low-dimensional space to predict the responses of the mapped candidate points.The candidate points with high constrained expected improvement values are selected for global exploration.Moreover,the local search process assisted by radial basis function and differential evolution is performed to exploit the design space efficiently.Several numerical benchmarks are tested to compare SADE-MLS with other algorithms.Finally,SADE-MLS is successfully applied to a solid rocket motor multidisciplinary optimization problem and a re-entry vehicle aerodynamic optimization problem,with the total impulse and lift to drag ratio being increased by 32.7%and 35.5%,respec-tively.The optimization results demonstrate the practicality and effectiveness of the proposed method in real engineering practices.

Evolutionary Computation for Expensive Optimization:A Survey

Expensive optimization problem(EOP) widely exists in various significant real-world applications. However, EOP requires expensive or even unaffordable costs for evaluating candidate solutions, which is expensive for the algorithm to find a satisfactory solution. Moreover, due to the fast-growing application demands in the economy and society, such as the emergence of the smart cities, the internet of things, and the big data era, solving EOP more efficiently has become increasingly essential in various fields, which poses great challenges on the problem-solving ability of optimization approach for EOP. Among various optimization approaches, evolutionary computation(EC) is a promising global optimization tool widely used for solving EOP efficiently in the past decades. Given the fruitful advancements of EC for EOP, it is essential to review these advancements in order to synthesize and give previous research experiences and references to aid the development of relevant research fields and real-world applications. Motivated by this, this paper aims to provide a comprehensive survey to show why and how EC can solve EOP efficiently. For this aim, this paper firstly analyzes the total optimization cost of EC in solving EOP. Then, based on the analysis, three promising research directions are pointed out for solving EOP, which are problem approximation and substitution, algorithm design and enhancement, and parallel and distributed computation. Note that, to the best of our knowledge, this paper is the first that outlines the possible directions for efficiently solving EOP by analyzing the total expensive cost. Based on this, existing works are reviewed comprehensively via a taxonomy with four parts, including the above three research directions and the real-world application part. Moreover, some future research directions are also discussed in this paper. It is believed that such a survey can attract attention, encourage discussions, and stimulate new EC research ideas for solving EOP and related real-world applications more efficiently.

Classification- and Regression-Assisted Differential Evolution for Computationally Expensive Problems

Differential Evolution （DE） has been well accepted ever, it usually involves a large number of fitness evaluations to as an effective evolutionary optimization technique. Howobtain a satisfactory solution. This disadvantage severely restricts its application to computationally expensive problems, for which a single fitness evaluation can be highly timeconsuming. In the past decade, a lot of investigations have been conducted to incorporate a surrogate model into an evolutionary algorithm （EA） to alleviate its computational burden in this scenario. However, only limited work was devoted to DE. More importantly, although various types of surrogate models, such as regression, ranking, and classification models, have been investigated separately, none of them consistently outperforms others. In this paper, we propose to construct a surrogate model by combining both regression and classification techniques. It is shown that due to the specific selection strategy of DE, a synergy can be established between these two types of models, and leads to a surrogate model that is more appropriate for DE. A novel surrogate model-assisted DE, named Classification- and Regression-Assisted DE （CRADE） is proposed on this basis. Experimental studies are carried out on a set of 16 benchmark functions, and CRADE has shown significant superiority over DE-assisted with only regression or classification models. Further comparison to three state-of-the-art DE variants, i.e., DE with global and local neighborhoods （DECL）, JADE, and composite DE （CODE）, also demonstrates the superiority of CRADE.

Effects of formal credit on pastoral household expense: Evidence from the Qinghai-Xizang Plateau of China

Formal credit is critical in agricultural production,allowing more expenditure and productive input,thereby improving farmers'welfare.In pastoral China,formal financial institutions are gradually increasing.However,a limited understanding remains of how formal credit affects herders'household expenses.Based on a survey of 544 herders from the Qinghai-Xizang Plateau of China,this study adopted the propensity score matching approach to identify the effect of formal credit on herders'total household expenses,daily expenses,and productive expenses.The results found that average age,grassland mortgage,and other variables significantly affected herders'participation in formal credit.Formal credit could significantly improve household expenses,especially productive expenses.A heterogeneity analysis showed that formal credit had a greater impact on the household total expense for those at higher levels of wealth;however,it significantly affected the productive expense of herders at lower wealth levels.Moreover,the mediating effect indicated that formal credit could affect herders'household income,thus influencing their household expenses.Finally,this study suggests that policies should improve herders'accessibility to formal credit.

Hybrid Meta-Model Based Design Space Differentiation Method for Expensive Problems

In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive points,with two different search strategies respectively applied inside and outside the promising region.Besides,the hybrid meta-model strategy applied in the search process makes it possible to solve the complex practical problems.Tested upon a serial of benchmark math functions,the HMDSD method shows great efficiency and search accuracy.On top of that,a practical lightweight design demonstrates its superior performance.

Carbamazepine in osteoarthritis treatment:A novel approach targeting Nav1.7 channels

Osteoarthritis(OA)presents a growing health concern,with substantial societal and healthcare burdens.Current management focuses on symptom relief,lacking disease-modifying options.Emerging research suggests the sodium channel Nav1.7 as a pivotal target in OA treatment.Preclinical studies demonstrate carbamazepine's efficacy in Nav1.7 blockade,offering significant joint protection in animal models.However,human trials are needed to validate these findings.Carbamazepine's repurposing holds promise for OA management,potentially revolutionizing treatment paradigms.Further research is essential to bridge the gap between preclinical evidence and clinical application,offering hope for improved OA management and enhanced patient quality of life.

Analysis of Hospitalization Costs and Influencing Factors of AKI in Adult Patients

Objective:To investigate the economic burden of patients with acute kidney injury(AKI)by analyzing the distribution of hospitalization expenses and its influencing factors in the Affiliated Hospital of Hebei University.Methods:The hospitalization information of patients with AKI from January 2020 to January 2023 was collected and sorted through the hospital charging system and the factors affecting the total hospitalization cost were analyzed by multiple linear regression.Results:Univariate analysis showed that age,occupation,marriage,length of hospitalization,recovery of renal function,and stage of AKI had significant effects on hospitalization cost(P<0.05).The result of the multiple linear regression analysis model showed that age(t=4.11,P<0.0001),length of hospitalization(t=16.10,P<0.0001),recovery of renal function(t=3.26,P<0.0001),AKI stage(t=5.23,P=0.002)are factors affecting the economic burden of patients with AKI.Conclusion:AKI patients should be managed according to age stratification to effectively control the progression of the disease and improve the quality of the medical services provided.This will reduce the economic burden of patients.

A Comparative Analysis of the Control Effect of Medical Expenses between General Hospitals and Traditional Chinese Medicine Hospitals from 2012 to 2021

Objective To analyze the changing trend of average medical expenses and structure in general hospitals and traditional Chinese medicine(TCM)hospitals and the effects and differences achieved by the two kinds of hospitals through controlling unreasonable growth of medical expenses,so as to provide reference for controlling the rapid rise of medical cost in public hospitals and optimizing the cost structure.Methods Based on the changes of related indicators of medical expense control from 2012 to 2021,the overall characteristics,changes of cost structure and trends of medical expenses in general hospitals and TCM hospitals were investigated.Results and Conclusion From 2012 to 2021,the increase of medical expenses in general hospitals and traditional Chinese medicine hospitals had slowed down,the proportion of drug revenue to medical income began to decline,and the medical service income increased.However,the proportion of inspection,test and sanitary materials income has increased instead of decreasing,but the management cost has decreased.The two kinds of hospitals have achieved certain cost control results,the structure of medical cost has changed greatly,and the technical service and labor value of medical personnel have been reflected to a certain extent.However,it is still necessary to explore a more scientific and reasonable cost control mechanism to promote the further optimization of medical cost structure.

Study on the Changes of Medical Income Structure in Governmentrun Hospitals of Traditional Chinese Medicine from 2012 to 2021

Objective To study the changing characteristics and trend of medical income structure in the government-run hospitals of traditional Chinese medicine(TCM),evaluate the effects of relevant reform measures,and to put forward corresponding suggestions for further optimizing their income structure.Methods The data related to the average medical income of government-run hospitals of TCM from 2012 to 2021 were sorted out.Then,descriptive analysis method was used to analyze the changes of related indicators.Besides,structural change method was applied to investigate the changes of outpatient income and inpatient income.Results and Conclusion From 2012 to 2021,the growth of medical income in government-run hospitals of TCM tended to be stable,and the proportion of medical service income increased from 22.62%(2012)to 29.38%(2021),but the average annual growth rate was only 0.68%.The main items that caused the change of outpatient income structure were medicine revenue,laboratory tests,diagnosis and treatment,and the cumulative contribution rate was 89.15%.The main items that caused the change of inpatient income structure were medicine revenue,sanitary materials,and auxiliary examinations income,with a cumulative contribution rate of 80.04%.However,the contribution rate of registration,diagnosis,treatment,surgery and nursing income reflecting the value of medical personnel’s technical labor was relatively small.The medical income structure of government-run hospitals of TCM underwent great changes and gradually became reasonable,but the medical service income increased slowly,and not all indicators achieved the expectations.To promote the sustainable development of public hospitals of TCM and enable them to provide high-quality and efficient TCM medical and health services,it is necessary to further improve the relevant policy mechanism.

Not Excessive,But Expensive

China's real estate market presents a dilemma. Demand for housing continues to climb, but so does the number of vacant houses as developers hold fast to prices that few urban residents can afford

Large-Scale Expensive Optimization with a Switching Strategy

Some optimization problems in scientific research,such as the robustness optimization for the Internet of Things and the neural architecture search,are large-scale in decision space and expensive for objective evaluation.In order to get a good solution in a limited budget for the large-scale expensive optimization,a random grouping strategy is adopted to divide the problem into some low-dimensional sub-problems.A surrogate model is then trained for each sub-problem using different strategies to select training data adaptively.After that,a dynamic infill criterion is proposed corresponding to the models currently used in the surrogate-assisted sub-problem optimization.Furthermore,an escape mechanism is proposed to keep the diversity of the population.The performance of the method is evaluated on CEC’2013 benchmark functions.Experimental results show that the algorithm has better performance in solving expensive large-scale optimization problems.

Top Ten Most Expensive 亿万富翁的玩具

其实,这个题目还有一个定义才算完整,那就是以美元为计量单位。怎么样,看到这里,你是否会觉得这些汽车有点贵得离谱了呢?

LIVIN’IT UP It's Expensive to Be Rich in Shanghai

Singapore might be where the film Crazy Rich Asians is set,but in terms of the most expensive city for luxury living,Shanghai is at the top of the list among all metropolises in the continent.

Hong Kong Ousts Tokyo as Most Expensive City

根据一家人力资源顾问公司(Mercer Human Resource Consulting)公布的全球生活指数调查的结果,香港的生活指数已经取代日本东京而成为全球生活指数最高的城市。第2位是莫斯科,东京则下跌为第3位。根据调查,香港生活指数上升,主要是个人护理、家居用品和交通项目费用高昂所致。调查同时研究了144个城市,比较其住房、食品、衣服、交通和娱乐等超过200项消费项目。在全球15个生活指数最高的城市当中,有11个位于亚洲,北京与上海分别排行第4位和第5位。调查发现,新西兰和澳大利亚的城市依然是生活费用便宜但生活质量最高的地方,大多数澳大利亚和新西兰城市的生活指数都在全球生活费用最高昂城市的一半以下。至于生活指数最低的城市则是南非的约翰内斯堡。布宜诺斯艾利斯(阿根廷首都)的生活指数则因国内经济不景气,而有一个dramatic fall。本文文字表达不乏可记学之处,如Moscow muscles in at secondplace in the survey一句中的muscles in就值得咀嚼一番。它是美国俚语,意思是:发挥臂力;靠力气前进,硬性挤入。另如:muscle through a crowd/用力挤过人群;muscle in on a

上海市耐多药结核病患者经济负担研究

目的基于上海市近年结核病诊疗费用减免政策,探索耐多药结核病(multidrug resistant tuberculosis,MDR-TB)患者疾病经济负担及其影响因素,为优化MDR-TB诊疗费用减免政策和综合管理模式提供依据。方法收集上海市2017—2019年确诊MDR-TB患者情况和诊疗费用减免情况数据,开展针对疾病经济负担的问卷调查,建立涵盖患者人口和社会经济情况、临床特征、疾病经济负担和诊疗费用减免情况数据库,明确患者疾病经济负担和灾难性卫生支出(catastrophic health expenditure)发生情况。以多元线性回归法分析可能影响患者疾病经济负担的因素,以多因素logistic回归法分析不同比例下灾难性卫生支出发生的影响因素。结果196例纳入研究分析的MDR-TB患者平均年龄为(44±16)岁,男性139例(占70.9%),上海户籍占46.4%,49%的患者为家庭主要劳动力。治疗期间,患者自付诊疗费用中位数为4.0(四分位数区间2.0~6.5)万元。113例患者获得减免诊疗,减免费用中位数为2.6(四分位数区间1.3~4.9)万元。若自付费用占家庭年收入的40%及以上,有47.8%的患者会发生灾难性支出;若不考虑减免政策,有59.8%的患者发生灾难性卫生支出。上海户籍(OR=0.3,95%CI为0.1~1.0)、更低家庭收入水平(P_(trend)=0.002)、医疗保险类型[(农村合作医疗保险/外来人口综合保险(OR=13.3,95%CI为1.0~171.2),无医疗保险(OR=17.5,95%CI为2.7~113.0)]和既往结核病治疗史(OR=3.3,95%CI为1.1~10.0)可能影响灾难性卫生支出的发生。结论上海市MDR-TB患者的自付诊疗费用较高。医疗保障力度较小和家庭经济情况不佳的患者更易发生高额自付费用,导致灾难性卫生支出。上海市MDR-TB诊疗费用减免政策有效降低了患者的经济负担。