scholarly journals New Combined Weighting Model Based on Maximizing the Difference in Evaluation Results and Its Application

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Bin Meng ◽  
Guotai Chi

This paper presents an approach for weighting indices in the comprehensive evaluation. In accordance with the principle that the entire difference of various evaluation objects is to be maximally differentiated, an adjusted weighting coefficient is introduced. Based on the idea of maximizing the difference between the adjusted evaluation scores of each evaluation object and their mean, an objective programming model is established with more obvious differentiation between evaluation scores and the combined weight coefficient determined, thereby avoiding contradictory and less distinguishable evaluation results of single weighting methods. The proposed model is demonstrated using 2,044 observations. The empirical results show that the combined weighting method has the least misjudgment probability, as well as the least error probability, when compared with four single weighting methods, namely, G1, G2, variation coefficient, and deviation methods.

2014 ◽  
Vol 521 ◽  
pp. 245-251
Author(s):  
Kai Xu ◽  
Xiao Yu Ding ◽  
Hong Wei Chen ◽  
Quan Yuan Jiang ◽  
Ke Sun ◽  
...  

With the number of power transmission and transformation projects increasing, it needs to consider more indices information and utilize more comprehensive evaluation methods in the decision-making of building schemes. As a consequence, a comprehensive evaluation indices system, including the indices of network security, economy, environmental friendliness, adaptation and coordination of the power transmission and transformation engineering system, is firstly built to evaluation construction schemes. Then this paper proposes a multi-attribute comprehensive evaluation method for power transmission and transformation projects. In this method, the optimal combination weighting method based on the moment estimation is adopted to weight for every index. It can overcome the weakness of the subjective weighting methods and the objective methods. After that, the optimal scheme is obtained by the grey correlation-cosine prioritizing evaluation method, which can take into account the distance and angle information of schemes. Finally, the example shows this method can fully consider overall information of each index, having good operability.


Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 269 ◽  
Author(s):  
Pengyu Chen

The entropy-weighting method (EWM) and variation coefficient method (VCM) are two typical diversity-based weighting methods, which are widely used in risk assessment and decision-making for natural hazards. However, for the attributes with a specific range of values (RV), the weights calculated by EWM and VCM (abbreviated as WE and WV) may be irrational. To solve this problem, a new indicator representing the dipartite degree is proposed, which is called the coefficient of dipartite degree (CDD), and the corresponding weighting method is called the dipartite coefficient method (DCM). Firstly, based on a large amount of statistical data, a comparison between the EWM and VCM is carried out. It is found that there is a strong correlation between the weights calculated by the EWM and VCM (abbreviated as WE and WV); however, in some cases the difference between WE and WV is big. Especially when the diversity of attributes is high, WE may be much larger than WV. Then, a comparison of the DCM, EWM and VCM is carried out based on two case studies. The results indicate that DCM is preferred for determining the weights of the attributes with a specific RV, and if the values of attributes are large enough, the EWM and VCM are both available. The EWM is more suitable for distinguishing the alternatives, but prudence is required when the diversity of an attribute is high. Finally, the applications of the diversity-based weighting method in natural hazards are discussed.


2021 ◽  
Author(s):  
Parjang Monajemi ◽  
Setareh Khaleghi ◽  
Shahrzad Maleki

Abstract In this research, a new conceptual model for producing instantaneous unit hydrographs (IUHs) is introduced by a linear combination of the Nash model, which assumes that the discharge from a reservoir is a linear function of its storage, and a model called inter-connected linear reservoir model (ICLRM), which assumes that the discharge from a reservoir is a linear function of the difference of its storage and its adjacent downstream reservoir. By employing these assumptions, a system of first-order linear differential equations with three degrees of freedom (storage coefficient, number of reservoirs, and weighting coefficient) is obtained as the governing equation for the proposed model. This model may be considered as the general form of the two models and is therefore capable of simulating IUHs laying between these two models. To show the capabilities of the model, linear and curvilinear soil conservation service (SCS) hydrographs are simulated using dimensionless hydrographs obtained by this model. Moreover, several real hydrographs were simulated by the proposed model and compared with hydrographs obtained by Nash, ICLRM, and SCS models. The results show that the model yields more accurate results compared to other studied models and may be considered as a new model for simulating IUHs.


2011 ◽  
Vol 291-294 ◽  
pp. 3349-3353
Author(s):  
Jin Hui Zhang ◽  
Zhi Wen Wang ◽  
Di Yuan

In this paper the entropy right-TOPSIS method is used, using entropy method to set weight is more effective than the use of subjective weighting method. The use of TOPSIS to determine evaluation scores can avoid the distribution of the number of samples and data limitations, reveals a different financial performance of listed companies the difference. From the evaluation results can be seen, N8, N5, N6, N7, N2 companies are the top five among the 12 listed companies. Their financial situation is better than other listed power companies.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.


2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.


2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.


Author(s):  
Koosha Choobdari Omran ◽  
Ali Mosallanejad

Purpose Double rotor induction machine (DRIM) is a particular type of induction machine (IM) that has been introduced to improve the parameters of the conventional IM. The purpose of this study is to propose a dynamic model of the DRIM under saturated and unsaturated conditions by using the equations obtained in this paper. Also, skin and temperature effects are considered in this model. Design/methodology/approach First, the DRIM structure and its performance will be briefly reviewed. Then, to realize the DRIM model, the mathematical equations of the electrical and mechanical part of the DRIM will be presented by state equations in the q-d axis by using the Park transformation. In this paper, the magnetizing fluxes saturation is included in the DRIM model by considering the difference between the amplitudes of the unsaturated and saturated magnetizing fluxes. The skin and temperature effects are also considered in this model by correcting the rotor and stator resistances values during operation. Findings To evaluate the effects of the saturation and skin effects on DRIM performance and validate the model, the machine is simulated with/without consideration of saturation and skin effects by the proposed model. Then, the results, including torque, speed, stator and rotor currents, active and reactive power, efficiency, power factor and torque-speed characteristic, are compared. In addition, the performance of the DRIM has been investigated at different speed conditions and load variations. The proposed model is developed in Matlab/Simulink for the sake of validation. Originality/value This paper presents an understandable model of DRIM with and without saturation, which can be used to analyze the steady-state and transient behavior of the motor in different situations.


2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jun Li ◽  
Qiang Dong ◽  
Yan Fu

As the rapid development of mobile Internet and smart devices, more and more online content providers begin to collect the preferences of their customers through various apps on mobile devices. These preferences could be largely reflected by the ratings on the online items with explicit scores. Both of positive and negative ratings are helpful for recommender systems to provide relevant items to a target user. Based on the empirical analysis of three real-world movie-rating data sets, we observe that users’ rating criterions change over time, and past positive and negative ratings have different influences on users’ future preferences. Given this, we propose a recommendation model on a session-based temporal graph, considering the difference of long- and short-term preferences, and the different temporal effect of positive and negative ratings. The extensive experiment results validate the significant accuracy improvement of our proposed model compared with the state-of-the-art methods.


2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.


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