Multi-objective design optimization of hybrid renewable systems using UGF

2015 ◽  
Vol 34 (6) ◽  
pp. 1825-1844 ◽  
Author(s):  
Carmen Delgado ◽  
José Antonio Domínguez-Navarro
Keyword(s):  
State Model ◽  
Computational Time ◽  
Renewable Generation ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Hybrid Generation ◽  
Content Type ◽  
Multi Objective ◽  
The Cost ◽  
The Impact

Purpose – Renewable generation is a main component of most hybrid generation systems. However, randomness on its generation is a characteristic to be considered due to its direct impact on reliability and performance of these systems. For this reason, renewable generation usually is accompanied with other generation elements to improve their general performance. The purpose of this paper is to analyze the power generation system, composed of solar, wind and diesel generation and power outsourcing option from the grid as means of reserve source. A multi-objective optimization for the design of hybrid generation system is proposed, particularly using the cost of energy, two different reliability indexes and the percentage of renewable energy as objectives. Further, the uncertainty of renewable sources and demand is modeled with a new technique that permits to evaluate the reliability quickly. Design/methodology/approach – The multi-state model of the generators and the load is modeled with the Universal Generating Function (UGF) to estimate the reliability indexes for the whole system. Then an evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm) is used to solve the multi-objective optimization model. Findings – The use of UGF methodology reduces the computation time, providing effective results. The validation of reliability assessment of hybrid generation systems using the UGF is carried out taking as a benchmark the results obtained with the Monte Carlo simulation. The proposed multi-objective algorithm gives as a result different generators combinations that outline hybrid systems, where some of them could be preferred over others depending on its results for each independent objective. Also it allows us to observe the changes produced on the resulting solutions due to the impact of the power fluctuation of the renewable generators. Originality/value – The main contributions of this paper are: an extended multi state model that includes different types of renewable energies, with emphasis on modeling of solar energy; demonstrate the performance improvement of UGF against SMC regarding the computational time required for this case; test the impact of different multi-states numbers for the representation of the elements; depict through multi-objective optimization, the impact of combining different energies on the cost and reliability of the resultant systems.

scholarly journals Comparison of Profit-Based Multi-Objective Approaches for Feature Selection in Credit Scoring

Algorithms ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 260
Author(s):  
Naomi Simumba ◽  
Suguru Okami ◽  
Akira Kodaka ◽  
Naohiko Kohtake
Keyword(s):  
Feature Selection ◽  
Selection Process ◽  
Credit Scoring ◽  
Computational Time ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Base Classifier ◽  
Grasshopper Optimization Algorithm ◽  
Specific Implementation ◽  
The Impact

Feature selection is crucial to the credit-scoring process, allowing for the removal of irrelevant variables with low predictive power. Conventional credit-scoring techniques treat this as a separate process wherein features are selected based on improving a single statistical measure, such as accuracy; however, recent research has focused on meaningful business parameters such as profit. More than one factor may be important to the selection process, making multi-objective optimization methods a necessity. However, the comparative performance of multi-objective methods has been known to vary depending on the test problem and specific implementation. This research employed a recent hybrid non-dominated sorting binary Grasshopper Optimization Algorithm and compared its performance on multi-objective feature selection for credit scoring to that of two popular benchmark algorithms in this space. Further comparison is made to determine the impact of changing the profit-maximizing base classifiers on algorithm performance. Experiments demonstrate that, of the base classifiers used, the neural network classifier improved the profit-based measure and minimized the mean number of features in the population the most. Additionally, the NSBGOA algorithm gave relatively smaller hypervolumes and increased computational time across all base classifiers, while giving the highest mean objective values for the solutions. It is clear that the base classifier has a significant impact on the results of multi-objective optimization. Therefore, careful consideration should be made of the base classifier to use in the scenarios.

Pareto-optimal front for multi-objective optimization of the suspension of a full-vehicle model in the frequency domain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Giovani Gaiardo Fossati ◽  
Letícia Fleck Fadel Miguel ◽  
Walter Jesus Paucar Casas
Keyword(s):  
Frequency Domain ◽  
Computational Time ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Vehicle Model ◽  
Content Type ◽  
Pareto Optimal Front ◽  
Multi Objective ◽  
Suspension Systems ◽  
Road Profile

PurposeThis study aims to propose a complete and powerful methodology that allows the optimization of the passive suspension system of vehicles, which simultaneously takes comfort and safety into account and provides a set of optimal solutions through a Pareto-optimal front, in a low computational time.Design/methodology/approachUnlike papers that consider simple vehicle models (quarter vehicle model or half car model) and/or simplified road profiles (harmonic excitation, for example) and/or perform a single-objective optimization and/or execute the dynamic analysis in the time domain, this paper presents an effective and fast methodology for the multi-objective optimization of the suspension system of a full-car model (including the driver seat) traveling on an irregular road profile, whose dynamic response is determined in the frequency domain, considerably reducing computational time.FindingsThe results showed that there was a reduction of 28% in the driver seat vertical acceleration weighted root mean square (RMS) value of the proposed model, which is directly related to comfort, and, simultaneously, an improvement or constancy concerning safety, with low computational cost. Hence, the proposed methodology can be indicated as a successful tool for the optimal design of the suspension systems, considering, simultaneously, comfort and safety.Originality/valueDespite the extensive literature on optimizing vehicle passive suspension systems, papers combining multi-objective optimization presenting a Pareto-optimal front as a set of optimal results, a full-vehicle model (including the driver seat), an irregular road profile and the determination of the dynamic response in the frequency domain are not found.

Investigation and optimization of textured thrust bearings with spirally distributed dimples using multi-objective optimization method

2020 ◽  
Vol 72 (6) ◽  
pp. 749-759
Author(s):  
Qiang Li ◽  
Yujun Wang ◽  
Shuo Zhang ◽  
Wei-Wei Xu ◽  
Lu Bai ◽  
...  
Keyword(s):  
Friction Force ◽  
Optimization Method ◽  
Loading Capacity ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Thrust Bearings ◽  
Multi Objective ◽  
Lubrication Performance ◽  
Distribution Parameters ◽  
The Impact

Purpose Surface textures have been widely used in thrust bearings as a means of enhancing the tribological performance. The effect of textures with a spiral distribution on the lubrication characteristics of thrust bearings has not been fully covered. This paper aims to investigate and find the optimal structure and distribution parameters of textures with the maximum loading capacity and minimum friction force as goals. Design/methodology/approach Combining the multi-objective optimization method based on the non-dominated sorted genetic algorithm-II with response surface methodology, the key textured parameters are optimized. Local sensitivity analysis is used to evaluate the impact level of each parameter. Findings Spiral distribution of textures can effectively improve the lubrication performance of the thrust bearing compared with the linear distribution. The distribution with high amplitudes and high cycle numbers will weaken the spiral effect and destroy the high-pressure region. Through the multi-objective optimization of the textured structure and distribution parameters, the loading capacity demonstrates a 55.05per cent improvement compared to the basic model. Textured width is the most sensitive parameter for both loading capacity and friction force. Originality/value Present research provides a fundamental design guide for textured thrust bearings.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

The impact of labor freedom on geographic cost of living differentials

2017 ◽  
Vol 6 (3) ◽  
pp. 385-395
Author(s):  
Richard Cebula ◽  
James E. Payne ◽  
Donnie Horner ◽  
Robert Boylan
Keyword(s):  
Labor Market ◽  
State Level ◽  
The State ◽  
Annual Data ◽  
Significant Finding ◽  
Cost Of Living ◽  
Content Type ◽  
The Usa ◽  
The Cost ◽  
The Impact

Purpose The purpose of this paper is to examine the impact of labor market freedom on state-level cost of living differentials in the USA using cross-sectional data for 2016 after allowing for the impacts of economic and quality of life factors. Design/methodology/approach The study uses two-stage least squares estimation controlling for factors contributing to cost of living differences across states. Findings The results reveal that an increase in labor market freedom reduces the overall cost of living. Research limitations/implications The study can be extended using panel data and alternative measures of labor market freedom. Practical implications In general, the finding that less intrusive government and greater labor freedom are associated with a reduced cost of living should not be surprising. This is because less government intrusion and greater labor freedom both inherently allow markets to be more efficient in the rationalization of and interplay with forces of supply and demand. Social implications The findings of this and future related studies could prove very useful to policy makers and entrepreneurs, as well as small business owners and public corporations of all sizes – particularly those considering either location in, relocation to, or expansion into other markets within the USA. Furthermore, the potential benefits of the National Right-to-Work Law currently under consideration in Congress could add cost of living reductions to the debate. Originality/value The authors extend the literature on cost of living differentials by investigating whether higher amounts of state-level labor market freedom act to reduce the states’ cost of living using the most recent annual data available (2016). That labor freedom has a systemic efficiency impact on the state-level cost of living is a significant finding. In our opinion, it is likely that labor market freedom is increasing the efficiency of labor market transactions in the production and distribution of goods and services, and acts to reduce the cost of living in states. In addition, unlike previous related studies, the authors investigate the impact of not only overall labor market freedom on the state-level cost of living, but also how the three sub-indices of labor market freedom, as identified and measured by Stansel et al. (2014, 2015), impact the cost of living state by state.

The impact of law, religion, and culture on the ease of starting a business

2018 ◽  
Vol 21 (4) ◽  
pp. 242-257 ◽  
Author(s):  
Dana L. Haggard ◽  
K. Stephen Haggard
Keyword(s):  
Economic Development ◽  
Political Stability ◽  
Cultural Dimension ◽  
Legal Origin ◽  
Content Type ◽  
Dynamic Factors ◽  
New Business ◽  
The Cost ◽  
The Impact ◽  
Starting A Business

Purpose The purpose of this paper is to examine the effects of culture, legal origin and religion on four measures of the ease of starting a new business; the number of procedures required, the number days required, the ease of getting credit and the cost to start a business. Design/methodology/approach The authors use linear regression to test the hypotheses using publicly available data on legal origin and religion from La Porta et al. (1999), cultural dimension information from Hofstede (2009) and measures of the ease of starting a business from the World Bank’s (2017) Doing Business Initiative. The final sample consists of 71 countries for which information was available on all the variables of interest. Findings Legal origin affects the number of procedures and the length of time needed to start a business, as well as the ease of getting credit. Culture (power distance) and religion are important for explaining gender differences in the ease of starting a business. The cost of starting a business is unrelated to culture, legal origin or religion. Originality/value Economic development is an important determinant of a country’s political stability and standard of living. Although politicians play a significant role in how a friendly a country is toward business, the study demonstrates that other longer-term and less dynamic factors have a material influence on economic development.

scholarly journals Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

2021 ◽  
Vol 336 ◽  
pp. 02022
Author(s):  
Liang Meng ◽  
Wen Zhou ◽  
Yang Li ◽  
Zhibin Liu ◽  
Yajing Liu
Keyword(s):  
Power Generation ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Solar Thermal ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Hybrid Power ◽  
Power Generation System

In this paper, NSGA-Ⅱ is used to realize the dual-objective optimization and three-objective optimization of the solar-thermal photovoltaic hybrid power generation system; Compared with the optimal solution set of three-objective optimization, optimization based on technical and economic evaluation indicators belongs to the category of multi-objective optimization. It can be considered that NSGA-Ⅱ is very suitable for multi-objective optimization of solar-thermal photovoltaic hybrid power generation system and other similar multi-objective optimization problems.

scholarly journals Mathematical modeling for optimizing the blood supply chain network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Rahimzadeh Dehaghani ◽  
Muhammad Nawaz ◽  
Rohullah Sultanie ◽  
Tawiah Kwatekwei Quartey-Papafio
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Nsga Ii ◽  
Content Type ◽  
Supply Chain Networks ◽  
Multi Objective ◽  
Blood Supply Chain ◽  
The Cost

PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.FindingsA novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.Originality/valueBy building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

scholarly journals Earnings quality and the cost of equity capital: evidence on the impact of legal background

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmed Hassan Ahmed ◽  
Yasean Tahat ◽  
Yasser Eliwa ◽  
Bruce Burton
Keyword(s):  
Earnings Quality ◽  
Institutional Ownership ◽  
Equity Capital ◽  
Cost Of Equity Capital ◽  
Cost Of Equity ◽  
Content Type ◽  
The Usa ◽  
The Uk ◽  
The Cost ◽  
The Impact

Purpose Earnings quality is of great concern to corporate stakeholders, including capital providers in international markets with widely varying regulatory pedigrees and ownership patterns. This paper aims to examine the association between the cost of equity capital and earnings quality, contextualised via tests that incorporate the potential for moderating effects around institutional settings. The analysis focuses on and compares evidence relating to (common law) UK/US firms and (civil law) German firms over the period 2005–2018 and seeks to identify whether, given institutional dissimilarities, significant differences exist between the two settings. Design/methodology/approach First, the authors undertake a review of the extant literature on the link between earnings quality and the cost of capital. Second, using a sample of 948 listed companies from the USA, the UK and Germany over the period 2005 to 2018, the authors estimate four implied cost of equity capital proxies. The relationship between companies’ cost of equity capital and their earnings quality is then investigated. Findings Consistent with theoretical reasoning and prior empirical analyses, the authors find a statistically negative association between earnings quality, evidenced by information relating to accruals and the cost of equity capital. However, when they extend the analysis by investigating the combined effect of institutional ownership and earnings quality on financing cost, the impact – while negative overall – is found to vary across legal backdrops. Research limitations/implications This paper uses institutional ownership as a mediating variable in the association between earnings quality and the cost of equity capital, but this is not intended to suggest that other measures may be of relevance here and additional research might usefully expand the analysis to incorporate other forms of ownership including state and foreign bases. Second, and suggestive of another avenue for developing the work presented in the study, the authors have used accrual measures of earnings quality. Practical implications The results are shown to provide potentially important insights for policymakers, creditors and investors about the consequences of earnings quality variability. The results should be of interest to firms seeking to reduce their financing costs and retain financial viability in the wake of the impact of the Covid-19 pandemic. Originality/value The reported findings extends the single-country results of Eliwa et al. (2016) for the UK firms and Francis et al. (2005) for the USA, whereby both reported that the cost of equity capital is negatively associated with earnings quality attributes. Second, in a further increment to the extant literature (particularly Francis et al., 2005 and Eliwa et al., 2016), the authors find the effect of institutional ownership to be influential, with a significantly positive impact on the association between earnings quality and the cost of equity capital, suggesting in turn that institutional ownership can improve firms’ ability to secure cheaper funding by virtue of robust monitoring. While this result holds for the whole sample (the USA, the UK and Germany), country-level analysis shows that the result holds only for the common law countries (the UK and the USA) and not for Germany, consistent with the notion that extant legal systems are a determining factor in this context. This novel finding points to a role for institutional investors in watching and improving the quality of financial reports that are valued by the market in its price formation activity.

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