A fuzzy optimum model to assess bridge design options

In the process of concept design of bridges, it is necessary to select the best from feasible alternatives through comparison and filter. The criterion set, used to evaluate and select the satisfying alternative, consists of many qualitative and quantitative factors. Therefore, the selection is a problem of multi-criteria and semi-structural decision making. Different from traditional methods in semi-structural decision making, a new framework and methodology is presented in this paper for evaluation of bridge alternatives. First the criterion set is established for the evaluation of alternatives. Next, the approach is studied to construct the relative membership degree matrix, in which both qualitative and quantitative factors are consistent with the uniform calculating standard. Then a new weight-assessing method is developed for calculation of the weights based on the relative membership degree matrix. Finally, a fuzzy optimum model is adopted to select the satisfying bridge alternative. Finally a case study is given to show the efficiency and robustness of the new framework and methodology.

Purpose In today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies. Design/methodology/approach A systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed. Findings For the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation. Practical implications From the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al ., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifying the qualitative measures, it is a challenging task to determine the optimal trade-off. In order to overcome these challenges, popular MCDM approaches, demonstrating effective results across different industries are discussed with their limitations and applications. Decision-makers can refer this study to identify best suitable decision-making technique for the MSS problem in the industry of their choice. Maintenance managers and engineers can refer the case studies illustrated in Tables 1 and 2 to analyse the MSS techniques proposed by previous studies with industry-specific applications. Social implications This study is an attempt to provide a reference point for research scholars interested in the field of maintenance management and/or development of maintenance strategy framework. This study provides a critical state-of-the-art review of efforts made in the field of MSS. The prominent maintenance strategies being implemented in contemporary industries are discussed with respective case studies. Interested researchers and academicians can familiarize themselves with these strategies and their distinct features in this study. In order to guide future studies and provide a reference point for academicians, MSS critical criteria used in extant literature are identified and classified into a comprehensive benchmark framework. Moreover, the industrial case studies are discussed with the most critical criteria of MSS for different industries and which strategy is most suitable for the respective industries based on these criteria. Table 1 presents different MCDM techniques and their hybrid applications for solving MSS problem that can help researchers in identifying research gaps. Future research can be directed at addressing the limitation of MCDM approach employed in existing studies and comparing the differences in results obtained by the proposed approach. Different industrial case studies with considered maintenance strategy alternatives are presented in Table 2, which can help researchers in identifying the industries that have not been studied yet. Moreover, not all of the existing studies are carried out by considering all the presented benchmark strategies, which can be addressed in future studies by interested researchers. More detailed discussion on research gaps is presented in the following section. Originality/value From the analysis of the extant literature, the authors could observe that the decision-making process adopted in numerous studies was limited to the classical maintenance strategies and not inclusive of aggressive maintenance strategy alternatives. To overcome these limitations and help maintenance managers in the decision-making, this study depicts the contemporary maintenance strategies, critical evaluation criteria and MCDM frameworks (employed to solve the MSS problem with industrial case studies) in a structured manner.

This article uses neural networks in forecasting stock market prices. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more accurately than current techniques such as technical analysis, fundamental analysis, and regression compared with neural network performance. Proposed intelligent stock market prediction system is based on the quantitative and qualitative factors. Three feedforward neural models can be used to analyze these factors. Input data to the neural network proposed are quantitative factors. Input data to the neural network proposed for qualitative factors can be factors related to the political effect considered. Third neural network consists of decision integration in which input data will be the outputs of above-mentioned neural networks. This facilitates to make right decision whether stock market is influenced by quantitative or qualitative factors

Fuzzy particle swarm optimization for conjunctive use of groundwater and reclaimed wastewater under uncertainty

Enterprise resource planning (ERP) adoption literature has a consensus that selecting the right ERP system is one of the most critical success factors in the ERP adoption lifecycle. While choosing a non-fitting ERP system may lead to adoption failures, however very few papers focus solely on this selection phase. Hence, given the criticality of the ERP selection phase, this paper aims to identify and review the different ERP selection methods in extant literature. This research also presents the factors and variables included in each identified selection method in ERP literature. As a result, each method identified was reviewed, analyzed, and summarized. Our main findings suggest that ERP selection is a multi-criteria decision-making (MCDM) problem, with various methods and techniques that can be utilized for such problems. Several MCDM methods have been used in literature, but often complementing more than one method combined at a time. This is since some methods excel in considering factors in uncertain environments, and other methods are best in evaluating qualitative and quantitative factors. Finally, while there are some methods that were used for cloud-ERP selections, there is no clear consensus in extant literature if some methods could best fit specifically cloud-ERP contexts in contrast to on-premises counterparts.

A fuzzy approach to the lectotype optimization of offshore platforms

Supplier selection is a Multi-Criteria Decision-Making problem in a supply chain involving many qualitative and quantitative factors. In this paper, an integrated approach using Analytic Hierarchy Process (AHP) and Fuzzy Linear Programming (FLP) is adopted for supplier selection and quota allocation problem. AHP is used to rate the suppliers, while FLP is used to allocate the quota to the suppliers. In FLP, multiple conflicting objectives with some constraints of buyers and suppliers are considered to optimise the order quantities. The ratings of suppliers, which are outputs of AHP, are used as inputs for Total Value of Purchase (TVP) where TVP is one of the objectives of FLP. Finally, sensitivity of the method has been analysed to understand the effect of variation in priority of selection criteria on suppliers' rating and then on quota allocation.

This paper presents a qualitative and quantitative research to explore and understand the agents that determine the level of productiveness and the importance of qualitative factors. A questionnaire was conducted to estimate the outcome of the qualitative agents or factors in improving the productivity of microtunneling projects. Information was collected from 26 competent professionals in microtunneling projects for almost 20years through an expert's opinion, using a semi-structured questionnaire. The Analytical Hierarchy Process and the clustering analysis technique have been used to account for the twenty qualitative agents or factors concerned in developing a proposed assessment model. The present research has developed an assessment model that stems from the result of qualitative factors on microtunneling to investigate the effect induced by the qualitative agents on productiveness. The assessment model is thereafter confirmed, showing an analytical outcome of 79.85% moderately justified percent. This study proved that the qualitative factors affecting the productivity of microtunneling projects can be assessed through the productivity index concept. This paper helps the industry parties to understand the factors influencing the success of microtunneling projects as well as, development of an assessment model to calculate productivity. Most of the past research on productivity models are based on quantitative factors only. This paper presents qualitative research to explore and understand the factors that affect productivity and the importance of qualitative factors. The developed assessment model presented is the first in connecting theory, analytical methods, and experts' opinions to help practitioners to understand and assess the productivity of microtunneling projects.

In this paper, we propose a new model for decision support to address the ‘large decision table’ (eg, many criteria) challenge in intuitionistic fuzzy sets (IFSs) multi-criteria decision-making (MCDM) problems. This new model involves risk preferences of decision makers (DMs) based on the prospect theory and criteria reduction. First, we build three relationship models based on different types of DMs’ risk preferences. By building different discernibility matrices according to relationship models, we find useful criteria for IFS MCDM problems. Second, we propose a technique to obtain weights through discernibility matrix. Third, we also propose a new method to rank and select the most desirable choice(s) according to weighted combinatorial advantage values of alternatives. Finally, we use a realistic voting example to demonstrate the practicality and effectiveness of the proposed method and construct a new decision support model for IFS MCDM problems.

Personnel selection is a complex, multi-criteria decision-making problem that involves both qualitative and quantitative factors. Despite various techniques being proposed across different industries, a robust method that adequately addresses uncertainty remains needed. This study introduces an integrated approach, combining the Step-wise Weight Assessment Ratio Analysis (SWARA) and the Double Normalization-Based Multiple Aggregation (DNMA) methods. The proposed framework first employs the SWARA method to determine the importance of criteria, followed by the application of the DNMA method to rank candidates based on a sequential evaluation process.The goal of the study is to select the most suitable candidate from five applicants for a vacant position in a company within the participatory software sector. The criteria weights were primarily determined by the decision-maker using the SWARA method, with computer and software skills, work experience, teamwork adaptability, foreign language proficiency, and problem-solving skills identified as the five key criteria. TheDNMA method was then used to assess the candidates' performance, and the results indicated that one of the candidates was the best fit for the position.When compared with similar studies in the literature, it was found that while many multi-criteria decision-making methods have been employed, the combination of SWARA and DNMA methods is novel. This study demonstrates the effectiveness of these methods in personnel selection, offering a new approach to the literature on decision-making processes.

The purpose of the study is to form an economic and mathematical instrument for assessing the role of quantitative and qualitative factors in changing the output of dairy products. Objectives: to determine the main theoretical provisions for calculating the indicator of dairy production depending on the resources used; to present a formalized expression for calculating quantitative factors of dairy output growth; to substantiate methodological tools for calculating qualitative, intensive factors of dairy output growth. The object of research is the scientific and technological development of the dairy subcomplex. The economic-mathematical and economic-statistical research methods were used. It has been established that the scientific and technological development of the dairy subcomplex is expressed, first of all, in an increase in the values of qualitative factors, the formal expression of which may be the values of labor productivity, capital productivity, yield or productivity; In periods with a constant level of technical development, quantitative factors receive priority - the number of workers, the cost of basic funds, the acreage, and the number of cows. A toolkit has been developed to assess the cumulative impact of both quantitative and qualitative factors on the resulting indicator of milk production, which will make it possible to reasonably assess the scientific and technological development of the dairy subcomplex. The qualitative factors include the productivity of the workers of the dairy subcomplex, the return on capital and the productivity of cows. Possible combinations of the influence of factors on the resulting indicator of milk production are determined. The key features of changes in influencing variables during periods with a constant level of technical development and in the context of the emergence of new, innovative technological solutions are characterized. Possible directions for further research to assess the scientific and technological de-velopment of the dairy-food subcomplex are outlined.

Exact [formula omitted]-optimal designs for a second-order response surface model on a circle with qualitative factors

Supply chain sustainability, which takes environmental, economic, and social factors into account, was recently recognized as a critical component of the supply chain (SC) management evaluation process and known as a multi-criteria decision-making problem (MCDM) that is heavily influenced by the decision-makers. While some criteria can be analyzed numerically, a large number of qualitative criteria require expert review in linguistic terms. This study proposes an integration of Data Envelopment Analysis (DEA), spherical fuzzy analytic hierarchy process (SF-AHP), and spherical fuzzy weighted aggregated sum product assessment (SF-WASPAS) to identify a sustainable supplier for the steel manufacturing industry in Vietnam. In this study, both quantitative and qualitative factors are considered through a comprehensive literature review and expert interviews. The first step employs DEA to validate high-efficiency suppliers based on a variety of quantifiable criteria. The second step evaluates these suppliers further on qualitative criteria, such as economic, environmental, and social factors. The SF-AHP was applied to obtain the criteria’s significance, whereas the SF-WASPAS was adopted to identify sustainable suppliers. The sensitivity analysis and comparative results demonstrate that the decision framework is feasible and robust. The findings of this study can assist steel industry executives in resolving the macrolevel supplier selection problem. Moreover, the proposed method can assist managers in selecting and evaluating suppliers more successfully in other industries.

A new ranking approach based on Grey Systems Theory using PROMETHEE II (Preference Ranking Organization METHod for Enrichment Evaluation II) is applied to a Multiple Criteria Decision Making (MCDM) problem. The objective is to rank alternative suggestions to decision makers for maintaining source water quantity and quality . The method uses grey sets to represent uncertain information in the PROMETHEE II method. An inherent advantage of this approach is its ability to comprehensively consider quantitative and qualitative factors, making reliable decisions in an environment of uncertainty and subjective information. In this case study, involving the evaluation of source water strategies in the Waterloo Region, located in Ontario, Canada, the linguistic values of alternatives are expressed as grey sets, which are used to aggregate the opinions of experts and stakeholders on the impacts of the strategies according to selected criteria.

The multi-criteria facilities layout problem can be formulated as a quadratic assignment model that can handle multiple qualitative and quantitative factors in the objective function. Some studies have shown that the techniques and tools of facilities layout problems can equally be applied for the layout design of user interface components in human-computer interface. This paper presents an alternate approach, which handles multiple qualitative and quantitative factors in a different manner separately in the objective function to obtain the initial layouts. The proposed approach also consists of a layout procedure, in which the pair of facilities with the least composite criterion value has been selected to be placed far apart in the layout to generate an initial layout in the construction procedure. The results of the proposed approach are compared with that of an existing approach which handles a number of qualitative and quantitative factors in the same manner as in the objective function to obtain the initial layouts for the example task of the user interface components layout problem under consideration.