Dynamic Multi-Attribute Decision-Making Method with Double Reference Points and Its Application

To better reflect the psychological behavior characteristics of loss aversion,this paper builds a double reference point decision making method for dynamic multi-attribute decision-making(DMADM)problem,taking bottom-line and target as reference pints.First,the gain/loss function is given,and the state is divided according to the relationship between the gain/loss value and the reference point.Second,the attitude function is constructed based on the results of state division to establish the utility function.Third,the comprehensive utility value is calculated as the basis for alternatives classification and ranking.Finally,the new method is used to evaluate the development level of smart cities.The results show that the new method can judge the degree to which the alternatives meet the requirements of the decision-maker.While the new method can effectively screen out the unsatisfactory alternatives,the ranking results of other alternatives are consistent with those of traditional methods.

Evaluating effectiveness of biological reference points for bigeye tuna (Thunnus obesus) and yellowfin tuna (Thunnus albacares) fisheries in the Indian Ocean

Biological reference point(BRP)is one of the essential components in the management strategy evaluation that is used to determine the status of fishery stock and set management regulations.However,as BRPs can be derived from different models and many different BRPs are available,the effectiveness and consistency of different BRPs should be evaluated before being applied to fisheries management.In this study,we used a computation-intensive approach to identify optimal BRPs.We systematically evaluated 1500 combinations of alternative BRPs in managing the bigeye tuna(Thunnus obesus)and yellowfin tuna(Thunnus albacares)fisheries in the Indian Ocean.The effectiveness and consistency of these BRPs were evaluated using four performance measures related to fisheries landing performance and biomass conservation.Monte Carlo simulation was used to evaluate various uncertainties.The results suggest that the proposed computation-intensive approach can be effective in identifying optimal BRPs with respect to a set of defined performance measures.We found that the current maximum sustainable yield(MSY)-based BRP combinations are effective target BRPs to manage the bigeye and yellowfin tuna fisheries with the“linear”harvest control rule(HCR).However,using the“knife-edge”HCR,better BRPs could be found for both the bigeye and yellowfin tuna fisheries management with improved fisheries and conservation performance.The framework developed in this study can be used to identify suitable BRPs based on a set of defined performance measures for other fisheries.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

A continuous time delay-difference type model(CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model(ASPM) and the surplus production model(SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore(T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore(T.alalunga) fishery.CTDDM obtained the 80%confidence interval of MSY(maximum sustainable yield) of(21 510 t,23 118 t).The catch in 2011(24 100 t) is higher than the MSY values and the relative fishing mortality ratio(F_(2011)/F_(MSY)) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

ADAPTIVE CONTROLLER AND ITS APPLICATION IN FORCE SYSTEM OF ASYMMETRIC CYLINDER CONTROLLED BY SYMMETRIC VALVE

Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.

Mathematical model for computing precise local tie vectors for CMONOC co-located GNSS/VLBI/SLR stations

The seven co-located sites of the Crustal Movement Observation Network of China（CMONOC） in Shanghai, Wuhan, Kunming, Beijing, Xi＇an, Changchun, and Urumqi are equipped with Global Navigation Satellite System（GNSS）, very long baseline interferometry（VLBI）, and satellite laser ranging（SLR） equipment. Co-location surveying of these sites was performed in 2012 and the accuracies of the solved tie vectors are approximately 5 mm.This paper proposes a mathematical model that handles the least squares adjustment of the 3D control network and calculates the tie vectors in one step, using all the available constraints in the adjustment. Using the new mathematical model, local tie vectors can be more precisely determined and their covariance more reasonably estimated.

A two scaled numerical method for global analysis of high dimensional nonlinear systems

This paper first analyzes the features of two classes of numerical methods for global analysis of nonlinear dynamical systems, which regard state space respectively as continuous and discrete ones. On basis of this understanding it then points out that the previously proposed method of point mapping under cell reference (PMUCR), has laid a frame work for the development of a two scaled numerical method suitable for the global analysis of high dimensional nonlinear systems, which may take the advantages of both classes of single scaled methods but will release the difficulties induced by the disadvantages of them. The basic ideas and main steps of implementation of the two scaled method, namely extended PMUCR, are elaborated. Finally, two examples are presented to demonstrate the capabilities of the proposed method.

某款新型白车身开发过程中工艺方案柔性化开发研究

文章主要描述了某款商用车在开发过程中,通过对产品,工艺,标准件,设备,工装,输送系统等通用化方案的优化,减少后期生产需要投入的设备、工装、输送系统等的数量,降低生产成本的投入。

AN AUTOMATED REFERENCE POINT-LIKE APPROACH FOR MULTICRITERIA SHORTEST PATH PROBLEMS

In this paper we introduce a method of analysis for the automated ordenng and selection or solutions of a multicriteria shortest path model. The method is based on a reference point approach, where the paths in a specific priority region are ranked by non-decreasing order of a Chebyshev metric. In order to list paths according with this objective function a labelling algorithm is proposed. The developed method is applied in a video-traffic routing context. Computational results are presented and analysed, for randomly generated networks of significant dimension.

A Note on“Prospect Theory and the Newsvendor Problem”

Based on the newsvendor setting,many behavioral models are proposed to predict the biases of decision makers in inventory management.Recently,Nagarajan and Shechter(Manag Sci 60:1057–1062,2014)claimed that prospect theory cannot explain the consistent empirical findings.However,it is noticed that their model is a special case of the general prospect theorymodel.In this note,we showthat the general prospect theory model may be powerful in predicting the preferences of decision makers in inventory management.

Projection bias, sophistication, and sub-additive discounting

Behavioral studies have revealed the sub-additive discounting pattern,which is at odds with the prevailing hyperbolic discounting framework that explains intertemporal choices.In this study,we demonstrate that completely and partially sophisticated individuals who are aware of their shifting preferences over time may exhibit sub-additive discounting behaviors.More importantly,these behaviors are not determined by whether an individual has hyperbolic time preferences or not.Instead,we show that the choices of reference points and partial projection bias may be the underlying drivers of the observed sub-additive discounting.