Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing time

The NP-hard scheduling problems of semiconductor manufacturing systems(SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance(such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule(SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.

Carbon Emissions Abatement(CEA)Allocation Based on Inverse Slack-Based Model(SBM)

Carbon emissions abatement(CEA)is an important issue that draws attention from both academicians and policymakers.Data envelopment analysis(DEA)has been a popular tool to allocate the CEA,and most previous works are based on radial DEA models.However,as shown in our paper,these models may give biased results due to their ignorance of slackness.To avoid such problems,we propose an allocation model based on the slack-based model and multiple-objective nonlinear programming to find the CEA allocation plan,which can minimize the GDP loss.The property of nonconvexity makes the model difficult to solve.Thus,we construct an approximation algorithm to solve this model with guaranteed error bounds and complexity.In the empirical application,we take regions of china as an illustrative example and find there is a significant region gap in China.Hence,we group the regions into eastern,central,and western,and give the main results,as well as the superiority of our allocation models compared with radial models.

中国沿海港口分层效率研究

为对处在不同效率层次的港口制定针对性决策,运用2014—2018年港口群的100个样本数据构建分层SBM-BPNN模型,该模型是基于松弛变量的测量(slack-based measure,SBM)模型与反向传播神经网络(back propagation neural network,BPNN)模型的结合。用构建的模型对2019年的港口群进行效率分层和决策制定。结果表明:分层SBM-BPNN模型不仅可以基于全体决策单元信息对分层SBM模型起替代作用,还可以在信息无法在各港口实时共享时,依据单个港口的信息对港口进行效率层次定位和分层最优决策的制定。分层效率研究有利于港口根据实际资源配置情况制定可行性较高的分阶段决策。

Urban Land Use Efficiency and Contributing Factors in the Yangtze River Delta Under Increasing Environmental Restrictions in China

Evaluating urban land use efficiency(ULUE) provides insights into the interactions between land use systems and their external environment. Specifically, changes in ULUE are important for monitoring urban transformation in developing countries. In this study, using a traditional input-output index model, we incorporated slack-based measurements and undesirable outputs into a SBM-UN(slack-based measure-undesirable) model to investigate ULUE within the context of increasing environmental restrictions in China. The model was used to estimate the ULUE of 26 cities in the highly developed urban agglomeration of the Yangtze River Delta from 2000 to2018. The average ULUE in the Yangtze River Delta was relatively low compared to that of developed city regions in the European Union(EU) and North America and exhibited a U-shaped curve over the study period. Incorporating undesirable outputs, such as environmental pollution, into the model reduced ULUE by 19.06%. ULUE varied spatially, with the kernel density estimation exhibiting a bimodal distribution. Efficiency decomposition analysis showed that scale efficiency made a greater contribution to ULUE than pure technical efficiency. Based on our findings, recommended approaches to improve ULUE include optimizing factor allocation, reducing undesirable outputs, and increasing the effective output per land unit. The study suggests that ULUE and the SBM-UN model are useful planning tools for sustainable urban development.

Super Efficiency and Misallocation: Evidence from Vietnamese Electric-Computer Industry

Misallocation means that the source is not distributed efficiently. This leads to an important question of how the relationship between misallocation and efficiency is (see [1]). The purpose of this study is to address the empirical relationship between misallocation and efficiency in the electric and computer industry in Vietnam during the 2005-2015 periods. To do this, we built a model that allowed us to evaluate the impact of misallocation and other factors on efficiency. The slack-based measured efficiency (SBM) model (Tone [2]), and the super-efficient model (Tone [3]) are used to estimate the firms’ efficiency. The approach of Hsieh and Klenow [4] is used to measure misallocation in the study area. Estimated results of the model about the relationship between misallocation and efficiency show that the variable representing the misallocation has a negative sign and statistical significance in all models. In other words, the misallocation negatively affects efficiency. The bigger the misallocation, the lower the efficiency.

Effect of building energy efficiency standards on carbon emission efficiency in commercial buildings

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions.Building energy efficiency standards(BEESs)are highly effective policies for reducing carbon emissions.Therefore,exploring the provincial variations in carbon emission efficiency(CEE)in the building sector and identifying the effect of BEESs on CEE is crucial.This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings.The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019.Furthermore,heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs.The results indicate that BEESs positively influence the CEE of commercial buildings.Specifically,a 1%increase in the intensity of BEESs causes a 0.1484%increase in the CEE of commercial buildings.Moreover,the impact of BEESs is particularly pronounced in the southern and western provinces.This study provides valuable scientific evidence for governments to enhance BEESs implementation.

中国省域绿色创新效率测度、差异分析及影响因素

绿色创新作为绿色发展和创新驱动战略的结合点,已成为全国绿色转型发展的重要战略目标。基于非期望产出的超效率SBM(slack-based measure)模型,对2012—2021年中国省域绿色创新效率测度评价,结合Dagum基尼系数对绿色创新效率进行差异分析,最后使用Tobit回归模型进行影响因素分析。研究结果表明:中国整体的绿色创新效率逐渐提高,但总的基尼系数呈现“W”型趋势,经济发展水平、市场竞争强度、对外开发水平和政府扶持力度均可显著提高绿色创新效率。根据研究结果,为提升绿色创新效率、缩小地区差异性提出对策建议。

Productivity Analysis for Banks' Merger and Acquisition Using Two-Stage DEA: Evidence from China

Mergers and acquisitions(M&A) are important parts of banking reform, which can increase the synergies and reduce the costs of the banks. To analyze the effect and importance of the M&A in the reform period, we measure the productivity change of China’s banks who completed M&A during 2004–2018, by using a two-stage data envelopment analysis(DEA) method. First, we incorporate the process of deposits producing and the process of profit earning as a two-stage structure of bank’s system. Then,we construct a slacks-based measure(SBM) model considering the weak disposability of undesirable outputs to measure the productivity of 14 M&A banks in China. Particularly, we adopt the global Malmquist index(GMI) to evaluate the productivity change of the banks, and analyze the efficiency change(EC) and technical change(TC) for the whole system and individual stages. Additionally, to facilitate making M&A plans, we classify the M&A banks to obtain the process they need to improve and the trend they could adopted:(i) We classify them into four categories by the productivity of two individual stages;(ii) We also classify them into four categories by EC and TC. Finally, the policy recommendations for M&A banks are given.