Research on Alliance Decision of Dual-Channel Remanufacturing Supply Chain Considering Bidirectional Free-Riding and Cost-Sharing

This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.

A Two-Stage Approach for Electric Vehicle Routing Problem with Time Windows and Heterogeneous Recharging Stations

An Electric Vehicle(EV)is an appropriate substitution for traditional transportation means for diminishing greenhouse gas emissions.However,decision-makers are beset by the limited driving range caused by the low battery capacity and the long recharging time.To resolve the former issue,several transportation companies increases the travel distance of the EV by establishing recharging stations in various locations.The proposed Electric Vehicle-Routing Problem with Time Windows(E-VRPTW)and recharging stations are constructed in this context;it augments the VRPTW by reinforcing battery capacity constraints.Meanwhile,super-recharging stations are gradually emerging in the surroundings.They can decrease the recharging time for an EV but consume more energy than regular stations.In this paper,we first extend the E-VRPRTW by adding the elements of super-recharging stations.We then apply a two-stage heuristic algorithm driven by a dynamic programming process to solve the new proposed problem to minimize the travel and total recharging costs.Subsequently,we compare the experimental results of this approach with other algorithms on several sets of benchmark instances.Furthermore,we analyze the impact of super-recharging stations on the total cost of the logistic plan.

Two-Stage Optimal Scheduling of Community Integrated Energy System

From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.

Solar-assisted two-stage catalytic membrane reactor for coupling CO_(2) splitting with methane oxidation reaction

A two-stage catalytic membrane reactor(CMR)that couples CO_(2) splitting with methane oxidation reactions was constructed based on an oxygen-permeable perovskite asymmetric membrane.The asymmetric membrane comprises a dense SrFe_(0.9)Ta_(0.1)O_(3-σ)(SFT)separation layer and a porous Sr_(0.9)(Fe_(0.9)Ta_(0.1))_(0.9)Cu_(0.1)O_(3-σ)(SFTC)catalytic layer.In thefirst stage reactor,a CO_(2) splitting reaction(CDS:2CO_(2)→2CO+O_(2))occurs at the SFTC catalytic layer.Subsequently,the O_(2) product is selectively extracted through the SFT separation layer to the permeated side for the methane combustion reaction(MCR),which provides an extremely low oxygen partial pressure to enhance the oxygen extraction.In the second stage,a Sr_(0.9)(Fe_(0.9)Ta_(0.1))_(0.9)Ni_(0.1)O_(3-σ)(SFTN)catalyst is employed to reform the products derived from MCR.The two-stage CMR design results in a remarkable 35.4%CO_(2) conversion for CDS at 900℃.The two-stage CMR was extended to a hollowfiber configuration combining with solar irradiation.The solar-assisted two-stage CMR can operate stably for over 50 h with a high hydrogen yield of 18.1 mL min^(-1) cm^(-2).These results provide a novel strategy for reducing CO_(2) emissions,suggesting potential avenues for the design of the high-performance CMRs and catalysts based on perovskite oxides in the future.

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.

Influence of two-stage harvesting on the properties of cold-pressed rapeseed(Brassica napus L.)oils

Rapeseed(Brassica napus L.)harvesting method is critical since it significantly determines the seed yield,oil quality,and industrial efficiency.This study investigated the influences of harvesting methods on the quality of cold-pressed rapeseed oil of two varieties.Oil color,peroxide value(POV),tocopherol content,fatty acid composition,and polarity of total polyphenols(PTP)contents of two rapeseed varieties in Huanggang and Xiangyang were compared through artificially simulated combined harvesting and two-stage harvesting.Results showed significant differences in the quality of rapeseed oil between the two harvesting methods.The red value(R-value),POV,total tocopherol contents,linoleic and linolenic acid content,and PTP content of the pressed rapeseed oil prepared by the combined harvesting method were about 27.6,5.7,15.8,2.0,0.5,and 28.6%lower than those of the oil produced from the two-stage harvesting method,respectively.Xiangyang and Huayouza62 performed better in the two regions and two varieties,respectively.To sum up,the rapeseed oil obtained 41–44 days after final flowering of combined harvesting,35 days after final flowering,and six days of post-ripening of the two-stage harvesting had the best quality.

Tourism Route Recommendation Based on A Multi-Objective Evolutionary Algorithm Using Two-Stage Decomposition and Pareto Layering

Tourism route planning is widely applied in the smart tourism field.The Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions problems,which leads to uneven distribution and weak diversity of optimization solutions of tourism routes.Inspired by these limitations,we propose a multi-objective evolutionary algorithm for tourism route recommendation(MOTRR)with two-stage and Pareto layering based on decomposition.The method decomposes the multiobjective problem into several subproblems,and improves the distribution of solutions through a two-stage method.The crowding degree mechanism between extreme and intermediate populations is used in the two-stage method.The neighborhood is determined according to the weight of the subproblem for crossover mutation.Finally,Pareto layering is used to improve the updating efficiency and population diversity of the solution.The two-stage method is combined with the Pareto layering structure,which not only maintains the distribution and diversity of the algorithm,but also avoids the same solutions.Compared with several classical benchmark algorithms,the experimental results demonstrate competitive advantages on five test functions,hypervolume(HV)and inverted generational distance(IGD)metrics.Using the experimental results of real scenic spot datasets from two famous tourism social networking sites with vast amounts of users and large-scale online comments in Beijing,our proposed algorithm shows better distribution.It proves that the tourism routes recommended by our proposed algorithm have better distribution and diversity,so that the recommended routes can better meet the personalized needs of tourists.

Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

Two-stage revision in periprosthetic knee joint infections

Periprosthetic joint infection(PJI)following total knee arthroplasty is one of the most catastrophic and costly complications that carries significant patient wellness as well as economic burdens.The road to efficiently diagnosing and treating PJI is challenging,as there is still no gold standard method to reach the diagnosis as early as desired.There are also international controversies with respect to the best approach to manage PJI cases.In this review,we highlight recent advances in managing PJI following knee arthroplasty surgery and discuss in depth the two-stage revision method.

A two-stage but time-saving reconstructive scheme to treat severe lower limb length discrepancy:Two case reports

Limb length discrepancy(LLD)is a common orthopedic condition that can result in significant functional impairment,pain,and cosmetic deformities.Current reconstructive techniques for severe LLD are primarily based on callus distraction,which is a time-consuming process that can lead to complications,such as significant infection,joint stiffness,and stress fractures.To reduce the therapeutic time and minimize the risk of complications,we investigated the use of vascularized bone flaps as a technical supplement to callus distraction in the reconstruction of short limbs.We present two cases of severe LLD in the upper and lower legs,in which a twostage reconstruction approach was used.In the first stage,external fixation was applied to the affected limb to correct the soft tissue length and convert the short deformity into a bone defect.In the second stage,the bone defect was reconstructed using bilateral(patient A)or unilateral(patient B)free vascularized fibula bone grafts.Both patients had complete survival of the fibular grafts without stress fractures,and bone consolidation took 8 months(patient A)and 4 months(patient B).Compared to the traditional callus distraction,the two-stage approach was found to be more time-saving and reliable.The entire reconstructive scheme required 18 and 4 months for patients A and B,respectively,whereas the traditional callus distraction required 41 and 17 months,respectively.These findings suggest that the use of vascularized bone flaps as a technical supplement for callus distraction may provide an effective and efficient alternative for the treatment of severe LLD.Further studies are needed to validate these results and assess the long-term outcomes of this approach.

A New Two-Stage Tunable Space-Time Adaptive Detector

In order to improve the rejection capability of mismatched interferer signals,a new two-stage detector is proposed under homogeneous scenarios with unknown covariance matrix,which is obtained by cascading the adaptive matched filter(AMF)detector and the enhanced RAO(EnRAO)detector.The new detector has constant false alarm performance,and the closed-form expression of probability of false alarm and probability of detection is derived.The performance of the new detector is assessed,and analyzed in comparison with other detectors.The results show that,the proposed detector can provide enhanced rejection capability in the case of mismatch,but the performance of the detector is slightly lost under the condition of matching.

Effect of quality uncertainty of parts on performance of reprocessing system in remanufacturing environment

Aimed at the problem of stochastic routings for reprocessing operations and highly variable processing times,an open queuing network is utilized to model a typical reprocessing system.In the model,each server is subject to breakdown and has a finite buffer capacity,while repair times,breakdown times and service time follow an exponential distribution.Based on the decomposition principle and the expansion methodology,an approximation analytical algorithm is proposed to calculate the mean reprocessing time,the throughput of each server and other parameters of the processing system.Then an approach to determining the quality of disassembled parts is suggested,on the basis of which the effect of parts quality on the performance of the reprocessing system is investigated.Numerical examples show that there is a negative correlation between quality of parts and their mean reprocessing time.Furthermore,marginal reprocessing time of the parts decrease with the drop in their quality.

An interacting multiple model-based two-stage Kalman filter for vehicle positioning

To address the problem that a general augmented state Kalman filter or a two-stage Kalman filter cannot achieve satisfactory positioning performance when facing uncertain noise of the micro-electro-mechanical system（MEMS） inertial sensors, a novel interacting multiple model-based two-stage Kalman filter（IMM-TSKF） is proposed to adapt to the uncertain inertial sensor noise. Three bias filters are developed based on different noise characteristics to cover a wide range of noise levels. Then, an accurate estimation of biases is calculated by the interacting multiple model algorithm to correct the bias-free filter. Thus, the vehicle positioning system can achieve good performance when suffering from uncertain inertial sensor noise. The experimental results indicate that the average position error of the proposed IMMTSKF is 25% lower than that of the general TSKF.

Remanufacturing production planning considering quality cost and demand substitution

Aiming to minimize the total production costs in a single planning period, a nonlinear integer programming model for remanufacturing production plans is established considering the influence of different qualities of returns acting on production cost. Three different remanufacturing and discarding strategies are adopted to analyze the change rules of the total production costs. The results returns is greater than indicate that when the number of remanufacturing returns of high the demand, preferentially quality and discarding those of low quality can bring better economic benefits due to manufacturing cost reduction. However, when the number of returns is smaller than the demand, there is no need to consider grading of returns, whereas new demand of remanufacturing. parts are required to satisfy the

Production of Light Olefins from Biosyngas by Two-stage Catalytic Conversion Process via Dimethyl Ether

NiSAPO-34 and NiSAPO-34/HZSM-5 were prepared and evaluated for the performance of dimethyl ether （DME） conversion to light olefins （DTO）. The processes of two-stage light olefin production, DME synthesis and the following DTO, were also investigated using biosyngas as feed gas over Cu/Zn/A1/HZSM-5 and the optimized 2%NiSAPO-34/HZSM- 5. The results indicated that adding 2%Ni to SAPO-34 did not change its topology structure, but resulted in the forming of the moderately strong acidity with decreasing acid amounts, which slightly enhanced DME conversion activity and C2=-C3= selectiw ity. Mechanically mixing 2%NiSAPO-34 with HZSM-5 at the weight ratio of 3.0 further prolonged DME conversion activity to be more than 3 h, which was due to the stable acid sites from HZSM-5. The highest selectivity to light olefins of 90.8% was achieved at 2 h time on stream. The application of the optimized 2%NiSAPO-34/HZSM-5 in the second-stage reactor for DTO reaction showed that the catalytic activity was steady for more than 5 h and light olefin yield was as high as 84.6 g/m3syngas when the biosyngas （H2/CO/CO2/N2/CH4=41.5/26.9/14.2/14.6/2.89, vol%） with low H/C ratio of 1.0 was used as feed gas.

Performance of bottleneck shifting for remanufacturing system considering returns' quality grading

Aimed at the remanufacturing system, the effect of the uncertainty of returns＇ quality on bottleneck shifting is investigated. A novel definition of bottleneck station is presented and the probability of a station becoming a bottleneck is also given. By calculating the effective output, the effective operation time （EOT） and the ratio of EOT of each station, the system＇s current bottleneck of effective output time is determined. By calculating the probability coefficient of variation and index of bottleneck shifting, the quantitative performance of bottleneck shifting is obtained. Discrete event simulation and the experiment design method are adopted to simulate the system, in which the proportion of quality grading, repair rates and process routes are considered. The case study shows that the uncertainty of returns＇ quality greatly increases the probability of bottleneck shifting, and with the increase of the discrete degree of the returns＇ repair rate, the bottleneck shifting phenomenon is more obvious. Furthermore, bottleneck shifting is closely related to the process route of the dominating returns＇ quality grade.

Facility location model for a remanufacturing logistics network

First a remanufactming logistics network is con- structed, in which the structure of both the forward logistics and the reverse logistics are of two levels and all the logistics facilities are capacitated. Both the remanufactming products and the new products can be used to meet the demands of customers. Moreover, it is assumed that homogeneous facilities can be designed together into integrated ones, based on which a mixed integer nonlinear programming （MINLP） facility location model of the remanufacturing logistics network with six types of facilities to be sited is built. Then an algorithm based on enumeration for the model is given. The feasible combinations of binary variables are searched by enumeration, and the remaining sub-problems are solved by the LP solver. Finally, the validities of the model and the algorithm are illustrated by means of an example. The result of the sensitivity analysis of parameters indicates that the integration of homogeneous facilities may influence the optimal solution of the problem to a certain degree.

基于Two-stage DEA-Tobit模型的中国省际竞技体育效率研究

基于Two-stage DEA的网络结构DEA方法,对我国31个省(直辖市、自治区)在第十二届全运会上的表现进行更深入的效率评价,并结合Tobit回归模型对影响竞技体育效率的社会环境因素进行分析.结果表明,全运会两个阶段中,仅山东省和西藏自治区为DEA有效的,AP阶段和AC阶段为DEA有效的地区分别为10个和3个,且提高各地区总效率的关键在于提高其AC阶段效率.从影响因素来看,地区经济水平与效率间存在负向影响,而体育场地资源配置及体育类支出是影响效率的主要因素,国民体质综合指数和体育投入规模对其无显著影响.

Remanufacturing system based on totally automatic MIG surfacing via robot

Remanufacturing system is a term of green system project which conforms to the national sustainable development strategy. With the demand of the high adaptability of the varieties of waste machining parts, the short product cycle, the low machining cost and the high product quality are offered. Each step of the remanufacturing system from the beginning of the scanning to the accomplishment of the welding was investigted. Aiming at building a remanufacturing system based on totally automatic MIG surfacing via robot, advanced information technology, remanufacturing technology and management, through the control of the pretreatment and the optimization to minimize the time of remanufacturing and realize the remanufacturing on the terminal products of varieties, were applied. The steps mainly include: 1) using the visual sensor which is installed at the end of the Robot to rapidly get the outline data of the machining part and the pretreatment of the data; 2) rebuilding the curved surface based on the outline data and the integrated CAD material object model; 3) building the remanufacturing model based on the CAD material object model and projecting the remanufacturing process; and 4) accomplishing the remanufacture of the machining part by the technology of MIG surfacing.

Advanced landfill leachate treatment using a two-stage UASB-SBR system at low temperature

A two-stage upflow anaerobic sludge blanket （UASB） and sequencing batch reactor （SBR） system was introduced to treat landfill leachate for advanced removal of COD and nitrogen at low temperature. In order to improve the total nitrogen （TN） removal efficiency and to reduce the COD requirement for denitrification, the raw leachate with recycled SBR nitrification supematant was pumped into the first-stage UASB （UASB1） to achieve simultaneous denitrification and methanogenesis. The results showed that UASB1 played an important role in COD removal and UASB2 and SBR further enhanced the nutrient removal efficiency. When the organic loading rates of UASB1, UASB2 and SBR were 11.95, 1.63 and 1.29 kg COD/（m^3.day）, respectively, the total COD removal efficiency of the whole system reached 96.7%. The SBR acted as the real undertaker for NH4^＋-N removal due to aerobic nitrification. The system obtained about 99.7% of NH4^＋-N removal efficiency at relatively low temperature （14.9-10.9℃）. More than 98.3% TN was removed through complete denitrification in UASB 1 and SBR. In addition, temperature had a significant effect on the rates of nitrification and denitrification rather than the removal of TN and NH4^＋-N once the complete nitrification and denitrification were achieved.