Multi-objective Optimization On The Basis Of Ratio Analysis Research Articles

Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

This paper delves into the development and validation of the RAMDOE method, a pioneering approach in multi-criteria decision making (MCDM) that seamlessly integrates the root assessment method (RAM) and design of experiments (DOE) techniques, addressing the inflexibility of traditional MCDM methods in accommodating adjustments in criteria ranges and the addition of new alternatives without necessitating a complete overhaul of the decision framework. Through empirical analysis, the study demonstrates the RAMDOE method's remarkable efficacy in precisely ranking alternatives, as illustrated through a practical case study focused on the selection of a supplier from a pool of seven candidates. One of the most notable aspects of the RAMDOE method lies in its capacity to formulate a regression equation that accurately captures the intricate relationship between alternative scores and criteria values, enabling decision-makers to seamlessly integrate new alternatives into the decision-making process without the cumbersome task of recalibration, thereby distinguishing it from conventional MCDM techniques such as TOPSIS (technique for order of preference by similarity to ideal solution), COPRAS (complex proportional assessment), MOORA (multiobjective optimization on the basis of ratio analysis), EDAS (evaluation based on distance from average solution) and CODAS (combinative distance-based assessment). The practical implications of these findings are profound, offering decision-makers across various domains a more efficient and adaptable framework to navigate complex decision scenarios. Particularly in contexts like supplier selection, where criteria ranges may vary significantly, the RAMDOE method provides decision-makers with a robust toolset to make informed decisions, presenting a promising avenue for addressing the dynamic nature of decision-making environments and enhancing the overall robustness and flexibility of MCDM processes in real-world applications

An integrated quantum picture fuzzy rough sets with golden cuts for evaluating carbon footprint-based investment decision policies of sustainable industries

The purpose of this study is to make evaluation related to the significant determinants of the effectiveness of the carbon footprint-based investments while constructing a novel decision-making model. At the first stage, selected five determinants are evaluated with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on quantum picture fuzzy rough sets. In the second part, sustainable industry alternatives are ranked by quantum picture fuzzy rough sets extended multi-objective optimization on the basis of ratio analysis (MOORA) technique. Similarly, elimination and choice translating reality (ELECTRE) approach is also taken into consideration to make a comparative evaluation. The main contribution of this study is that a novel methodology is proposed by integrated picture fuzzy row sets and quantum theory. While using the combination of rough sets and picture fuzzy logic, uncertain data in the complex process can be evaluated in a more effective manner. Moreover, due to the criticisms to stepwise weight assessment ratio analysis (SWARA) methodology by not considering causal relationship of the determinants, this methodology is extended with the help of some improvements so that a new approach (M-SWARA) is proposed to overcome this deficiency by creating impact direction map of the items. The ranking results of these two techniques are the same that indicates the coherency of the findings. It is concluded that carbon-free project financing with green bonds is the most important indicator for this situation. On the other side, the ranking results demonstrate that renewable energy investment is the most appropriate sustainable industry alternative. Considering the results obtained in this study, the development of green bonds should be given priority. Establishing an international certification system is important in terms of clearly defining green bonds. Government supports are also of critical importance in the development of green bonds. Tax reductions provided by governments can increase the profitability of green bonds. This may contribute to investors showing more interest in green bonds.

Enhancing efficiency in photo chemical machining: a multivariate decision-making approach

Non-Traditional Machining (NTM) outperforms traditional processes by offering superior geometric and dimensional accuracy, along with a better surface finish. Photo Chemical Machining (PCM) represents one such NTM process, using chemical etching for material removal. PCM finds substantial application in the creation of microchannels in pharmaceutical, chemical and energy industries. Several input parameters—such as etchant concentration, etching time and etchant temperature—profoundly influence the machining’s quality and efficiency. Therefore, the optimization of these parameters is crucial. This study presents a comparative analysis of five Multiple Criteria Decision Making (MCDM) techniques—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), Additive Ratio Assessment (ARAS), Weighted aggregated sum product assessment method (WASPAS) and Multi-Attributive Border Approximation Area Comparison Method (MABAC)—for the optimization of the PCM process. Key performance metrics considered are Material Removal Rate (MRR), Surface Roughness (SR), Undercut (Uc) and etch factor (EF). The weights of these criteria were calculated using the Criterion-Induced Aggregation Technique (CRITIC) and was compared with other popular methods like MEREC, Entropy and equal weights. MRR and EF are seen as beneficial criteria, while SR and Uc are perceived as cost criteria. Optimum process parameters were identified as 850 g/L etchant concentration, 40 min etching time and 70°C etchant temperature. Two of the three employed MCDM techniques agreed on these optimal parameters, reinforcing the findings. Furthermore, a strong correlation was observed amongst the employed MCDM techniques, further validating the results.

Evaluation of Health Systems Performance of OECD Countries Using MOORA Method

International comparison of health systems performance provides evidence to countries, policymakers and decision-makers. This study was conducted in order to rank and compare the health systems performance levels of the Organization for Economic Development and Cooperation (OECD) countries according to the determined health performance indicators. In the study, the data of the countries between the years of 2000–2017 were used and evaluated. The study consists of 36 member countries of the OECD. The data was analysed with the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method, which is one of the multi-criteria decision-making methods, allowing the comparison of the performance of health systems across countries is compared. As a result of the health system performance evaluations of OECD countries. As a result of the health system performance evaluations of OECD countries, it has been concluded that countries such as Switzerland, Germany and Sweden have a high level of health systems performance, and Mexico, Colombia and Turkey have a lower performance compared to other countries. It is expected that countries with lower health system performance levels due to health system structures, demographic characteristics, education levels and technological development levels can still develop by selecting alternative countries suitable for their purpose and adopting the policies and strategies of such countries to their own systems.

Towards Efficient Energy Solutions: MCDA-Driven Selection of Hybrid Renewable Energy Systems

In these days of growing awareness on Renewable Energy Sources and their benefits, there is a major issue that needs to be considered, which is selection of suitable Hybrid Renewable Energy System (HRES) among the vast multitude of choices. In this paper, multiple Multi Criteria Decision Analysis (MCDA) techniques are proposed to select the best among a choice of six HRES Systems using different criteria including but not limited to net present cost (NPC), operating cost, renewability fraction, CO2 & NOx emissions etc. The criteria weights are obtained using Analytical Hierarchy Process (AHP) based on the preference order of the criteria. The decision matrix is obtained from the statistical data of the different HRES and using different MCDA techniques such as Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), rankings are given to the HRES systems based on their closeness to the ideal solution. These rankings are helpful in the selection of suitable HRES configuration for normal household purposes. Since cost aspects are given greater preference, the obtained rankings lean more towards economically affordable solutions without compromising on the number of units generated.

Decision Support System for Performance Assessment of Honoray Personnel Applying MABAC, MOORA, and ARAS Method with a Combination of ROC Weighthing

MABAC (Multi-Attributive Border Approximation area Comparison), ARAS (Additive Ratio Assessment), and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) are decision support system methods employed for evaluating the performance of honorary staff. MABAC utilizes a multi-attribute border approximation area approach to measure the relative performance of honorary staff. ARAS assigns weights to competing attributes and produces assessment ratio values aiding in decision-making. Meanwhile, MOORA focuses on multi-objective optimization by considering ratio analysis. The combination of these three methods provides a holistic and comprehensive framework for assessing the performance of honorary staff, enabling decision-makers to effectively evaluate their contributions and achievements based on predefined criteria. This approach allows for the determination of relative rankings and the selection of honorary staff that best align with organizational needs

The Optimal Sustainable Insulation Material by Using MCDM Analysis

Increasing fuel costs is the new norm, and an increase in energy consumption leads to many troubles, such as a growing of harmful environmental emissions and rise in energy consumption bills. Hence, it’s desirable and recommended to estimate the value of energy consumed for buildings in the first design state in order to reduce the impact of these issues, and obtain a sustainable building using thermal insulation for the buildings (walls, roofs, floors...).
 The purpose of this experimental analysis is to determine the best insulating material among 12 selected materials, as the properties of these materials were analysed based on several criteria.
 The study focuses on using multiple analysis methods in order to achieve the best results and to eliminate potential inconsistencies of data with available scientific methods. The evaluation is conducted via implementing three multiple criteria decision-making methods (MCDM)the full Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) multiplication, rating the choices and selection the solution nearest to ideal, VIekriterijumsko KOmpromisno Rangiranje (VIKOR) and the method of ordering options by analogy with the optimal method (TOPSIS). In addition to the significance of the criteria, find the weights of the criterion in the analysis by using the correlation between criteria (CRITIC). Results based on pre-established methods showed consistent results, with the highest and worst performing materials identified in buildings. Extruded polystyrene foam (XPS) is ranked the best among other materials. The number of articles related to MCDM isn’t that high. Therefore, this study will contribute to filling the gap.

Combination of Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) and Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) in Determining the Best Cashier

MOORA (Multi-Objective Optimization by Ratio Analysis) method is one of the multi-criteria analysis techniques used for alternative selection based on several different criteria or objectives. In the context of selecting the best cashier, by using the MOORA method to select cashiers based on several relevant criteria. While Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) is a method used to assess the importance of criteria relative to each other in the context of multi-criteria analysis. This method helps in determining the weight of criteria used in multi-criteria decision making. The combination of MOORA and PIPRECIA will produce the best cashier selection based on the criteria used. The results of the best cashier assessment ranking using the Multi-Objective Optimization method on the basis of Ratio Analysis (MOORA) and the Simplified Pivot Pairwise Relative Criteria Importance Assessment weighting method obtained results, namely for Rank 1 obtained by Rini Maya with a final value of 0.343.

The Implementation of MOORA method in the Selection of Direct Cash Aid Recipients

This research aims to implement the Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) algorithm as a Decision Support System for selecting recipients of Direct Cash Assistance in Cempaka Putih village, Gorontalo. With a dataset of 112 prospectus recipients, the study focuses on developing an efficient approach to assist the village head in the beneficiary selection process. By combining multi-objective optimization and ratio analysis, the MOORA algorithm objectively evaluates and ranks recipients based on eligibility and suitability. The findings demonstrate the effectiveness of MOORA in streamlining the selection process, ensuring transparency and optimizing resource allocation for those most in need. This research contributes to decision support systems by showcasing the practical application of MOORA, enhancing assistance distribution, and improving community welfare. The results show that Alternative A1 receives the highest ranking, which is 1, with a Yi value of 1.32. Therefore, Alternative A1 is recommended as the best candidate to receive direct cash assistance in the Cempaka Putih village. The method has the capability to rank the top 12 suitable candidates who are eligible to obtain direct cash aid. However, there are instances where certain Yi values match, resulting in the same ranking for those alternatives. This similarity necessitates further observation and analysis.

Decision Support System for Determining the Best Pesticide for Rice Plants Using the Moora Method

completed quickly and performed effectively and efficiently, especially in the agricultural sector. Pesticides are chemical or organic substances that farmers use to protect rice plants from pests , so farmers often have difficulty choosing pesticides that will be used to prevent rice pests. In fact, the large number of pesticide products on the market and their very different advantages make farmers confused in determining pesticide choices. The Harapan Jaya farmer group always provides counseling and training regarding the management of agricultural products, therefore the farmer group continues to maintain rice production to avoid pests and there is no shortage of rice plants at this time by using pesticide products on the market. Decision Support Systems (DSS) are systems that are able to provide problem solving abilities and communication abilities for problems with structured and unstructured conditions. The method in the decision support system is Multi Objective Optimization on the basis of Ratio Analysis (MOORA). The results obtained from this calculation method are Rodenticide with a value of 0.288 which is ranked first and the fifth rank is Insecticide with a value of 0.047. By implementing a decision support system using the MOORA method, it is hoped that it will help select interconnected outputs, because the decision results are based on criteria data in determining the best pesticide for rice plants

Decision Support for Sustainable Energy Choices: An MCDM Framework for High Renewable Energy System (HRES) Selection

This research project utilizes Multi-Criteria Decision-Making (MCDM) techniques, specifically Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), to enhance the selection of High Renewable Energy Systems (HRES). As global environmental concerns intensify, HRES selection becomes pivotal for sustainable energy solutions. The project's primary objective is to furnish decision-makers with a structured framework that accommodates numerous criteria and objectives. Initially, an extensive set of criteria, spanning environmental, economic, and technical aspects of HRES, is established. AHP assigns relative weights to these criteria, ensuring a well-informed decision-making process. Subsequently, TOPSIS ranks HRES alternatives based on their performance against these criteria, yielding a shortlist of viable HRES solutions. MOORA extends the analysis by addressing conflicting objectives within the decision-making process, accommodating both maximization and minimization objectives. Combining insights from AHP, TOPSIS, and MOORA offers a comprehensive overview of the most appropriate HRES alternatives. This holistic approach equips decision-makers with valuable information on trade- offs and benefits, facilitating the selection of HRES solutions that align with diverse goals. By leveraging these MCDM methods, this project promotes systematic and informed HRES selection, fostering the advancement of sustainable energy solutions and contributing to a greener future. Key Words: MCDM; AHP; TOPSIS; MOORA; HRES.

Komparasi Metode Maut dan Moora dalam Pemilihan Sunscreen untuk Kulit Menggunakan Pembobotan ROC

The skin is the outer layer of the human body that has various important functions. However, high sun exposure in Indonesia can cause damage to the skin due to ultraviolet rays. The use of sunscreen becomes important in preventing sunburn and skin cancer. Women with combination skin types often have difficulty choosing the right sunscreen. This study applies the Multi Attribute Utility Theory (MAUT) and Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) methods with the weighting of the Centroid Rank Order (ROC) method and the level of accuracy of MSE aims to produce decisions in choosing the right sunscreen for combination skin. At the methodology stage, data on criteria, sub-criteria, and alternatives are collected through observation and interviews. The criteria consist of 6 namely Benefit, Composition, Price, Vitamins, Side Effects, and Size. The ROC is used for weighting, while the MAUT and MOORA methods are used in the assessment and comparison of alternatives and MSE is used for the level of accuracy. The discoveries from this study hold the possibility to offer recommendations for choosing the best sunscreen for combination skin, namely A7 with the brand sunscreen Somethinc Comfort Correct for the MAUT method is 0.7134 and the MOORA method is 0.102. The results of the MSE calculation obtained a deviation value, namely the MOORA method with a value of 215.0091 better than the MAUT method of 207.4922. So that the MOORA method is the best method in choosing sunscreen for combination skin and aims to help people who are still having difficulty choosing the right sunscreen, so as to avoid mistakes in choosing inappropriate sunscreens that can have a negative impact on the skin

Financial accounting the role of Information Technology in accounting change Using MOORA (Multi-objective Optimization on the basis of Ratio Analysis) Method

financial accounting, Financial accounting is a financial related to business summary of transactions, analysis, and reporting related is a branch of accounting. Available for public use preparing financial statements this includes. Partners, suppliers, banks, employees, government agencies, business owners, and other partners decisions making such for purposes for those interested in getting information examples. Financial accounting local and international accounting managed by standards. Generally accepted accounting principles (gaap) in any jurisdiction for financial accounting used standard of guidelines framework. Accountants’ registration and summary and financial position in preparing reports standards that follow, traditions and the rules include. Financial accounting is a specific type of accounting this is from business activities actions that arise documenting for time, summarizing, and includes reporting. Such transactions balance sheet, income statement, and cash flow statement in preparing accounts, including outlined, they are the company's financial results during a period document. A fund public to the accountant and work in private sectors there may be opportunities. Finance accountant's duties a from the general accountant differentiated, he is a company or for himself rather than organization or work for himself or for himself doing. Financial accounting created accounting uses a set of standards. To be used by a financial accountant accounting standards are required the selection company will face regulatory and reporting depending on requirements. In india, indian chartered accountants accounting provided by the company ( icai ) standards used. These are substantially i.f.mr.s standards are based and agree. However, accounting and i.f.mr.s between certain principles there are some differences. Versatile with unique alternatives a new method for optimization is proposed MOORA (multi-objective based on ratio analysis optimization. This method is objective denotes the matrix of responses of the alternatives, however, proposing better policies, which rates are used. Well established. Multi-objective another method for optimization is used for comparison, reference point method. Then, various competition this proved to be the best choice among the methods. Accounting standards goodwill impairment, accounting standards segment reporting, Accounting standards FA principles in budgets/forecast, Performance measurement, Transfer pricing. Primary field of accounting, Ultimate purpose of accounting, Function of accounting, Domain of Convergence, Mode of convergence, Role of IT in convergence. From the result it is seen that Role of IT in convergence is got the first rank where as is the Primary field of accounting is having the lowest rank. Role of IT in convergence is ranked first and Primary field of accounting is ranked lowest.

The Analysis of Cyber security in Intelligent Transportation Systems Using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Method

Cyber security has become a critical concern in today's interconnected world, with the escalating frequency and sophistication of cyber threats. To effectively protect digital assets and sensitive information, organizations must adopt robust cybersecurity systems. The Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method has emerged as a promising approach for evaluating and improving cybersecurity systems.This research presents an innovative application of the MOORA method to enhance cybersecurity systems. The MOORA method is a Multi-Criteria Decision Analysis (MCDA) technique that enables decision-makers to rank alternatives based on multiple criteria, ultimately aiding in selecting the most suitable solution. In the context of cybersecurity, various evaluation criteria are considered, such as threat detection accuracy, incident response time, scalability, resource utilization, and cost-effectiveness.Through the integration of the MOORA method, this study offers a systematic and quantitative assessment of cybersecurity systems, addressing the limitations of traditional evaluation techniques that often overlook the complexity of cyber threats. By prioritizing the criteria most relevant to an organization's specific needs and risk profile, decision-makers can make informed choices about investing in the right cybersecurity measures.The practical implementation of the proposed MOORA-based cybersecurity system is demonstrated using real-world data from a diverse set of organizations. The results showcase the effectiveness of the method in guiding cybersecurity decision-making, leading to the identification of optimal solutions that strike the best balance between performance, cost, and resource allocation.The alternatives are A1 is Providing only essential information and continuing to use the service or product, A2 is Giving wrong or partially wrong information as personal data (misinformation), A3 is Closing the account, disposing of, or deactivating the smart device or application and A4 limiting the use of the application, financial institution, or device. The Evaluation parameters are C1 is Low trust in the firm, device, or application, C2 is Poor referrals or negative word-of-mouth from previous users about the service or app, C3 is Negative previous online experience, C4 is Being tech-savvy, experienced, and knowledgeable about recent trends in data privacy and cybersecurity, C5 is The firm or institution not meeting essential privacy and security expectations, such as privacy policies, notices (cookies), seals, etc and C6 is Perceiving that the benefits outweigh the risks of disclosing information.The final result is Limit the use of application, financial institution or device, etc (A4) is got first rank and Provision of strictly necessary Information and continue the use of service or product (A1) is got lowest rank.

E-Commerce Supply Chain Optimization with the MOORA Method and Certainty Factor

This study analyzes supply chain optimization on e-commerce platforms by applying the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) and Certainty Factor methods. The aim of this research is to gain in-depth insights into the relative performance of e-commerce platforms in the context of predefined criteria and sub-criteria. The research methodology consists of six stages, including data collection, selection of criteria and sub-criteria, application of Certainty Factor, selection of case studies, relative analysis using MOORA, and certainty level analysis using Certainty Factor. The results of the analysis show that these two methods provide valuable insights regarding the performance of e-commerce platforms. The MOORA method provides a relatively strong rating, while the Certainty Factor provides an additional dimension by considering the level of certainty regarding the factors that affect performance. From a comparison of the results of the two methods, platforms such as Tokopedia.com and Shopee consistently rank well in both analyses. The implication of this research is that the e-commerce platform has greater development potential in supply chain optimization efforts. Overall, the integration of the MOORA and Certainty Factor methods has succeeded in providing more detailed and comprehensive insights into supply chain optimization on e-commerce platforms. This research provides guidance for stakeholders in making more informed and directed decisions regarding supply chain optimization strategies in e-commerce platforms

Recruitment of TikTok Live Hosts for Selling Clothes Using the MOORA Method

Mistakes in recruiting Hosts for the business of selling clothes on TikTok live streaming can have a negative impact on business owners, because Host failure can cause the products offered not to sell to potential customers. To overcome this problem, a decision support system is needed as a support tool for clothing selling entrepreneurs in recruiting TikTok Live Hosts that are relevant and can contribute to the development of their business. In this study the authors used Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) for the TikTok Live Host recruitment process with 5 (five) alternatives and 5 assessment criteria in subjective decision making. The results of this study indicate that the alternative that gets the first ranking position and is recommended to be accepted as a TikTok Live Host is A5 (Rina) with a value of 0.2752. As for the ranking order of other alternatives, namely A1 (Janses) with a value of 0.2738 at rank 2, A3 (Aisyah) with a value of 0.2582 at rank 3, A4 (Kylen) with a value of 0.2460 at rank 4, and A2 (Delima) with a value of 0.2190 at rank 5.

Effect of Ghatti gum content on mechanical properties of epoxy composite using multicriteria optimization techniques

In the recent years particles-based composites are more attractive due to many of the applications. The reinforcing of particles, micro or nano powders enhanced the properties by crosslinking with polymers. The partial based polymer composites are playing a major role in enhancing the strength of pure resins. In many of common particle reinforcements materials are fly ash, Nano clay, silica powders etc… these are more predominately used to enhance the properties of the pure resin and even with fiber reinforced composites. This paper focuses on the effect of microns size natural powder reinforcement in synthetic resin to evaluate the tensile, flexural, impact and hardness properties behavior of composites. The Gum Ghatti which is obtained from the plant and processed to obtain the powder. The 5, 10, 15 and 20 % of gum Ghatti natural powders are reinforced in Araldite LY 556 (Bisphinol-A-Diglycidyl-ether) epoxy resin to observe the mechanical strength and interfacial adhesion strength between matrixes with reinforcement materials. These composites are post-cured at 80℃ for three hours to improve the residual stresses. The 10% natural particular reinforcement exhibits better tensile and flexural properties as compared to other compositions. However, Barcol hardness number of 15 percentage of reinforcements shows better. These mechanical properties are further analyzed using MCDM techniques to identify best weight fraction. The Preference Selection Index (PSI), Multiobjective Optimization on The Basis of Ratio Analysis (MOORA), Combinative Distance-based Assessment (COMDAS), VIekriterijumsko KOmpromisno Rangiranje (VIKOR), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are used and observed that 10% gum Ghatti exhibited better mechanical properties.

Risk Identification Model for Lean Manufacturing Improvement

Small- and medium-sized manufacturing enterprises (SMEs) were confronted with a variety of difficulties due to the increasingly complex market environment, and many of them could not make enough profits to proceed with their manufacturing tasks. The objective of this study was to develop a model of risk management by integrating several risk tools at manufacturing companies. This study was also intended to improve the decision making by providing quantitative analysis at each step of risk management and improve lean practices. Risk quantitative analysis methods such as failure modes and effects analysis (FMEA) and multi-objective optimization on the basis of ratio analysis (MOORA) were applied in this study to identify the potential risks. Moreover, the risk assessment was used to categorize risks into different severity levels. The manufacturing data obtained from a case study was utilised to calculate the risk priority number (RPN). The risk mitigation actions were formulated to reduce the original RPN and the final RPN value decreased to a normal standard in the end. Overall, this study optimised the risk management of one case study SME and improved lean manufacturing practices. By establishing the risk identification model and applying common lean manufacturing concepts in reducing wastes at actual manufacturing processes, the manufacturing enterprise could manage to optimize the operations and increase the actual manufacturing productivity. The machining and assembly processes of diesel engines were optimized and improved with the decrease of RPN and the selection of the CK6150 CNC lathe that owns the highest MOORA assessment value.

A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making

A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making

Electric Vehicle Solar Charging Station Siting Study Based on GIS and Multi-Criteria Decision-Making: A Case Study of China

Electric vehicles (EVs) are one of the most practical solutions to the energy issue and environmental pollution. In recent years, EVs have developed rapidly, but are still limited by charging problems. The emergence of photovoltaic charging stations can solve the environmental pollution and charging problems. The location of charging stations is critical in the life cycle of electric vehicles. In this paper, a multiple-criteria decision-making (MCDM) method based on Geographic Information Technology (GIS) for optimal site selection is proposed. First, based on literature reading and expert interviews, a site selection index system was identified, including four aspects with a total of ten sub-criteria. Secondly, a spatial database of relevant evaluation criteria was established using GIS, and preliminary analysis was conducted. Then, the fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory method) is applied for assigning the criteria weights. Then, potential sites are ranked using the fuzzy MULTIMOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method. Then, the model was validated by siting the electric vehicle PV charging stations in Qingdao, and eight stations were identified in the preliminary selection stage, and the most suitable locations were finally selected through the MCDM stage. Finally, the reliability and validity of the model were further verified by comparative analysis and dual sensitivity analysis.