Fuzzy Technique For Order Performance By Similarity To Ideal Solution Research Articles

Evaluating Lecturer Performance in Vietnam: An Application of Fuzzy AHP and Fuzzy TOPSIS Methods

Higher education is regarded as being of paramount importance in Vietnam and as being essential to raising the level of the country's labor force and promoting economic progress. Evaluation of lecturers is one of the institution's activities and a crucial component of managing human resources in higher education institutions. How to evaluate faculty members' overall performance using a range of criteria is one of the key evaluation-related challenges. This study presents a method that uses fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to assess and rank the performance of lecturers. Specifically, the evaluation framework is developed by identifying criteria and sub-criteria based on a comprehensive review of existing literature. Following that, the fuzzy AHP approach is used to determine the weights of the criteria and sub-criteria using the pairwise comparisons. The Fuzzy TOPSIS approach is employed to assess and prioritize lecturers identified through expert evaluation. When applied in group decision-making, utilizing fuzzy AHP and fuzzy TOPSIS promotes agreement among decision-makers and diminishes uncertainty in decision-making processes. The utilization of the multiple criterion measurement approach can then be used to carry out the evaluation. The suggested framework is also demonstrated via a case study. The use of this framework can improve the evaluation's objectivity, accuracy, and scientific methodology. It is believed that this work will assist managers of higher education institutions improve their standards for educational quality.

Performance measurement of factors affecting consumer experience in healthcare services using fuzzy and grey techniques

PurposeThe importance of consumer experience in service industries, particularly healthcare, is widely acknowledged as it captures the intricacies of quality management. In tandem with the emerging research trends that evaluate service excellence through user experience, this study renders a performance analysis of the dimensions of consumer experience that individually or collectively shape healthcare consumers’ perceptions of service quality.Design/methodology/approachA cross-sectional study was conducted across 13 mid-tier corporate hospitals to collect data from 438 patients. The data was processed through factor analysis in SPSS to confirm sample adequacy and factor extractability. Further, two independent multi-criteria decision-making (MCDM) tools, Fuzzy Technique for Order Performance by Similarity to Ideal Solution (F-TOPSIS) and Grey Relational Analysis (GRA), were executed to render performance analysis of identified factors.FindingsUsing F-TOPSIS, factors such as “information” and “hospital environment” received higher performance ratings, while items related to “communication with doctors” and “humanistic care” received lower rankings. Minor yet anticipated deviations were observed while verifying performance scores using GRA. Nonetheless, both outcomes exhibited a strong correlation coefficient of 97.14%, confirming analytical consistency.Originality/valueHitherto, such usages of hybrid MCDM techniques have rarely been executed to convey a clear understanding of consumers’ experiences in healthcare services. Moreover, the findings provide a clear insight into consumers’ key response areas, which can further be translated to maximize consumer gratification, thus assisting healthcare managers in improving service performance and clinical decision-making.

Adaptive Multi-Criteria-Based Load Balancing Technique for Resource Allocation in Fog-Cloud Environments

Recently, to deliver services directly to the network edge, fog computing, an emerging and developing technology, acts as a layer between the cloud and the IoT worlds. The cloud or fog computing nodes could be selected by IoTs applications to meet their resource needs. Due to the scarce resources of fog devices that are available, as well as the need to meet user demands for low latency and quick reaction times, resource allocation in the fog-cloud environment becomes a difficult problem. In this problem, the load balancing between several fog devices is the most important element in achieving resource efficiency and preventing overload on fog devices. In this paper, a new adaptive resource allocation technique for load balancing in a fog-cloud environment is proposed. The proposed technique ranks each fog device using hybrid multi-criteria decision- making approaches Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS), then selects the most effective fog device based on the resulting ranking set. The simulation results show that the proposed technique outperforms existing techniques in terms of load balancing, response time, resource utilization, and energy consumption. The proposed technique decreases the number of fog nodes by 11%, load balancing variance by 69% and increases resource utilization to 90% which is comparatively higher than the comparable methods.

Temporary safety zone site selection during haze Pollution: An integrated approach with FAHP and FTOPSIS

Haze pollution poses significant health risks, driving organizations to mitigate its impact. Temporary safety zones are essential for protecting people during haze pollution incidents. However, current strategies may fall short in meeting demand under certain conditions. To address this challenge and aid decision-making, we propose a methodology for selecting temporary safety zone sites during haze pollution. The methodology integrates the Fuzzy Analytic Hierarchy Process (FAHP), the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS), and a fuzzy mathematical model. Criteria for site selection are established through literature reviews and expert interviews and the FAHP assigns weights to each criterion. FTOPSIS evaluates candidate locations based on the criteria, generating scores for each site. Finally, a multi-objective fuzzy mathematical model identifies optimal locations, considering budget limits, capacity restrictions, and other constraints. We validated the approach in the Sarapee district in Thailand. The results demonstrate the model’s ability to generate optimal solutions, identifying suitable locations for temporary safety zones during haze pollution crises. This research is significant for decision-makers and governments who need to strategically place temporary safety zones and safeguard communities from the hazards of haze pollution. By adopting this integrated approach, organizations can enhance their response to haze pollution incidents, protecting public health and well-being.

A novel fuzzy SECA model based on fuzzy standard deviation and correlation coefficients for resilient-sustainable supplier selection

Selecting the best out of a pool of potential suppliers is one of the most significant challenges in supply chain management. Although numerous works have studied supplier selection (SS) as a function of individual criterion (e.g., sustainability or resiliency), few studies have explored it as an all-in-one. To address this gap, this study proposes a novel fuzzy multi-criteria decision-making (MCDM) framework for a real-world color and glaze case study. First, resilient-sustainable criteria are identified for evaluating the performance of the suppliers. Expert opinions and literature review are then utilized to establish a set of criteria in two different categories: sustainability and resiliency. This two-pronged approach ensured that important criteria are considered in the evaluation process. Next, a new fuzzy simultaneous evaluation of criteria and alternatives (FSECA) model is developed to highlight the most crucial criteria and the best supplier. The proposed model utilizes a predetermined set of criteria reference weights as benchmarks to calculate the final weights that closely align with these reference points. Moreover, the consideration of fuzzy standard deviation and correlation coefficients of fuzzy numbers are incorporated to take into account the inherent variability and uncertainty in the data, resulting in a more accurate and robust analysis of the data. To validate the proposed method, the findings are compared to the state-of-the-art fuzzy approaches for SECA method, and other MCDM techniques such as fuzzy weighted aggregated sum product assessment (FWASPAS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), fuzzy Multi-Objective Optimization on the basis of Ratio Analysis (FMOORA), fuzzy simple additive weighting (FSAW), and fuzzy complex proportional assessment (FCOPRAS). Moreover, by applying the geometrical analysis for interactive aid (GAIA), a visualization approach, the results demonstrate that the performance of the proposed framework is satisfactory and highlight the most crucial criteria, such as the supplier responsiveness in resiliency and delivery in economic impact of sustainability categories. Since choosing supplier is a strategic decision, the proposed work can help managers to choose the right suppliers.

A fuzzy TOPSIS model for selecting digital technologies in circular supply chains

Several digital technologies are available to facilitate the transition toward a circular supply chain infrastructure. Small-Medium Enterprises (SMEs) should assess their readiness and measure their performance to select the most appropriate digital technology. This study explores how well-established digital technologies such as Cyber-Physical Systems (CPS), the Internet of Things (IoT), Cloud Manufacturing (CM), and Big Data Analytics (BDA) impact circular supply chain infrastructure in SMEs. Questionnaires have been distributed to collect employees’ preferences concerning the circular supply chain management criteria (profit, innovation, sustainability, and optimization). The responses have been organized into three clusters using Principal Component Analysis (PCA). A fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) technique is adopted to evaluate these technologies since it constitutes a reliable managerial tool when vagueness impacts the smooth operation of the supply chain. Results indicate the ranking order of the investigated digital technologies (CPS>IoT>CM>BDA) as well as the circular benefits and the supply chain attributes imparted upon implementing these technologies. Such benefits and attributes are provided to assess the impact of these digital technologies on a circular economy. Lastly, the perspective of the selection process affected by other factors, such as the enterprise’s extroversion level and its internal structure, are discussed.

Ranking Strategic Goals with Fuzzy Entropy Weighting and Fuzzy TOPSIS Methods: A Case of the Scientific and Technological Research Council of Türkiye

This study involves an integrated approach consisting of the Fuzzy AEW Method which considers all relevant criteria and involves the contribution of all members of a strategic planning team in the determination of strategic goals as well as the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. The Fuzzy AEW method has been used in weighing the criteria whereas the Fuzzy TOPSIS method has been used in determining the order of the alternatives. This article presents a real-world case using this model in setting targets for improving the institutional capacity of the Scientific and Technological Research Council of Türkiye (TÜBITAK). In this study, strategic goals have been set forth considering the opinion of strategic planning experts and previous strategic plans, and then the said method has been applied. The model could easily be applied both in the public and private sectors. This new model involves the effective planning of scarce resources and ensures digitalization in planning as well as the determination of goals through analytical methods. Ineffective meetings and workshops of the past will be replaced by a participatory and transparent structure.

A systematic assessment of multi‐dimensional risk factors for sustainable development in food grain supply chains: A business strategic prospective analysis

AbstractThe food grain supply chain (FGSC) is composed of several links, stretching from the point of production to the point of consumption. A broken connection might produce a food catastrophe. The structural imbalance of India's FGSC is an obstacle to achieving sustainability; this has to be addressed if the country is to preserve national food security. This present study aims to develop a systematic assessment of the risks and the priority of risk‐mitigating solutions in attaining sustainability in the Indian FGSC. Multiple groups of individuals and businesses involved in the FGSC have been surveyed and interviewed, with their responses analyzed. A total of 31 risk factors and 11 risk‐reduction strategies are identified. Further, the identified risk factors are classified into five‐dimensional sustainability criteria (environmental, economic, institutional, technical, and social) by using exploratory factor analysis (EFA). Then, a fuzzy analytical hierarchy process (FAHP), combined with the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method, is adopted to find the most critical risk factors and choose the best course of strategies for risk mitigation. The study finds that inability to incorporate advanced technology imposes the highest risk to sustainability followed by natural disasters. Ensuring end‐to‐end computerization using advanced technology like agri 4.0 is the need of the hour in intercepting the range of FGSC risks. The results may help policymakers create a comprehensive risk mitigation plan and taxonomy to increase supply chain resilience.

Improved formal safety assessment methodology using fuzzy TOPSIS for LPG-fueled marine engine system

In this study, a risk assessment of a Liquefied Petroleum Gas (LPG) marine engine system being developed for installation in the first LPG-powered ship in South Korea was performed and a new standard for a formal safety assessment (FSA) was proposed. Based on the FSA technique, hazards were identified through a failure mode and effect analysis (FMEA) in the first stage. An FMEA workshop was conducted to assess 110 components, and 89 hazards were identified. Of these, 19 failure modes of intolerable level were identified, and risk ranks were divided into four groups. Then, a more objective risk assessment was conducted using fuzzy set theory to compensate for the subjectivity of FMEA. Additionally, a technique for order performance by similarity to ideal solution (TOPSIS) was used to represent the risk rank of individual systems more precisely. By the second stage, risk ranks could be divided into 28 groups through the classification of a total of 89 hazards. Finally, risk control options were presented for high-ranking hazards according to the fuzzy TOPSIS results, and a cost-benefit analysis was performed. Consequently, the gross and net costs of averting a fatality were calculated as US $2.98 million and US $2.93 million, respectively. Through a cost-benefit analysis, the periodic exchange of main critical components was found to be in the range of economic criteria that could be recommended as a safety standard. The risk assessment technique proposed in this study allows a more objective and effective selection of critical hazards that necessitate risk control measures.

An Integrated Approach with CLFPR-Based ANP and Fuzzy TOPSIS for Evaluating Business Performance of Rural Homestays: Study from China

Given the high importance of the performance of rural homestays to the local economy, this study aims to fill the gap in homestay performance research and make rural homestays more competitive and sustainable after the coronavirus disease epidemic (COVID-19). Integrating a consistent linguistic fuzzy preference relations-based analytic network process (CLFPR-based ANP) and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS), this study constructs a comprehensive evaluation model of the performance of rural homestays and empirically analyzes homestay performance in Zhejiang. The results show the following: (1) Among the criteria’s weights by CLFPR-based ANP, homestay operation and management, service quality, and homestay geist and community co-prosperity should be given much more attention; the importance of factors regarding the environment and building of rural homestays is gradually weakening. (2) In light of ranking alternatives based on performance evaluation by fuzzy TOPSIS, the homestay with the optimal performance has been found, which practitioners can use as a benchmark. Therefore, the priorities of these criteria further deepen the understanding of the performance of rural homestays and underline the development direction for practitioners. Simultaneously, in terms of feasibility and reliability, the integrated approach comprises a beneficial attempt and becomes an effective evaluation tool for practitioners to improve effectiveness.

Evaluation of quality of online shopping services in times of COVID-19 based on E-S-QUAL model and Fuzzy TOPSIS method.

This paper aims to propose an approach to evaluate the quality of online shopping services in times of pandemic COVID-19, from the ordering of quality attributes taking into account customers' perception. The proposed approach was developed from a structured questionnaire containing 25 quality attributes adapted from the E-S-QUAL model and applied to consumers of online shopping services. Fuzzy set theory was used in the approach to simplify the subjectivity of human judgment, along with the extension of Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). Therefore, this research was classified as applied, exploratory, quantitative and survey. To achieve the research objective, 819 questionnaires were collected. Among the main findings, it is highlighted that the attributes "product availability", "products with excellent quality", "confidence in online shopping processes" and "ease of buying online" were the ones that presented the best perceptions of quality by the respondents. At the other end, the attributes "opinion sharing on social networks", "buying online is a good option when you have little time", "distraction in online shopping searches" and "shopping online is a pleasure" showed the highest level of dissatisfaction with the service. Thus, this article highlights the importance of online shopping services in times of the pandemic caused by COVID-19, and its main contribution and originality is the development of an approach that aims to support the decision-making process, establishing strategic actions for the continuous improvement of online shopping services with the reduction of subjectivity in customer perception and with successive refinements.

Selection of Business Process Modeling Tool with the Application of Fuzzy DEMATEL and TOPSIS Method

The business process modeling tool selection problem has a significant impact on the overall performance of enterprise business process modeling, which will directly affect the development of enterprise information systems. Apart from that, the process to select the business process modeling tool from all alternatives is a Multi-Criteria Decision Making (MCDM) problem. This paper develops a methodology based on the hybrid fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method to help companies select the optimal business process modeling tool, where the business process modeling process is more efficient, economic and safe. The proposed method has the following state-of-the-art contributions and features: (1) the latest application of the MCDM methodology to the field of BPM tool selection, (2) addressing the direct and indirect impact between criteria in the selection of BPM tools, and (3) considering the hybrid fuzzy (uncertainty) decision-making issue in the BPM tool selection process. Meanwhile, the mathematical formula in TOPSIS can be regarded as a formula for solving a symmetric problem. The hybrid fuzzy DEMATEL method is used to obtain the weight for the criteria to be considered in the BPM tool selection process, and the TOPSIS method is used to obtain the final business process modeling tool.

A Fuzzy AHP-Fuzzy TOPSIS Urged Baseline Aid for Execution Amendment of an Online Food Delivery Affability

The increased demand for this form of food delivery has been expected to drastically alter restaurant patrons’ dining habits. As people have been forced to stay indoors to prevent the virus from spreading, food delivery services over the internet are in high demand. As established in this study, the planned ideal is a good executive implementation for online meal delivery services. Food delivery services are rapidly growing in India, opening up several opportunities for a wide range of online food delivery (OFD) platforms while also generating a competitive commercial sector. Following that, the fuzzy technique for order performance by similarity to ideal solution method (FTOPSIS) is used to rank online food delivery (OFD) enterprises based on the characteristics chosen. In this paper, we study the present multi-criteria decision-analysis (MCDA) paradigm based on the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method to achieve the goal. After that, a hierarchy multiple criteria decision-analysis (MCDA) model based on fuzzy sets theory is introduced to deal with the online food delivery Service in the chain system. The fuzzy analytic hierarchy process (FAHP) is a fuzzy set theory technique for generating criteria weights, which are then used to interpret expert phonological evaluation statements.

A hybrid multi-criteria decision-making approach for analysing operational hazards in Heavy Fuel Oil-based power plants

Hazard identification and prioritisation practices are very important for power plants to continue their operations without disruption. Systematic operational hazard analysis is not a very common practice at the Heavy Fuel Oil (HFO) based power plants in Bangladesh. Hence, a structured hazard evaluation framework can greatly benefit them to ensure their operational safety. This study has been conducted to identify and prioritise the operational hazards of the HFO-based power plants through using a hybrid multi-criteria decision-making (MCDM) approach in a fuzzy environment, and then, to explore the appropriate mitigation methods for the top-ranked hazards and to find the interrelationships that exist among the mitigation methods. First, the most common hazards in HFO-based power plants have been identified from the expert feedbacks. Then, a fuzzy analytical hierarchy process (FAHP) method has been used to determine the weights of the evaluation criteria and a fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method, has been used for the final ranking of the potential hazards. Afterwards, mitigation methods for the top 25 hazards have been identified and interrelationship among those mitigation methods has been explored through using interpretive structural modelling (ISM) and a matriced impacts croisés multiplication appliquée à un classement (MICMAC) analysis. The study finds that ‘explosion of high-pressure steam drum of the gas boiler’, ‘crankcase explosion and fire hazard due to oil pressure rise’ and ‘explosion of the compressed air reservoir’ are the top three hazards in the hazard ranking. ‘Standard operating procedure (SOP) and training’ have been found to be the most driving mitigation methods for the top-ranked hazards based on the ISM-MICMAC analysis. The findings of this study are expected to provide the managers of power plants with valuable insights, which can help them to prepare sustainable operational strategies to ensure the least hazardous work environment.

Prioritizing the Potential Smartification Measures by Using an Integrated Decision Support System with Sustainable Development Goals (a Case Study in Southern Italy)

With the increasing population of cities, expanding roads as one of the essential urban infrastructures is a necessary task; therefore, adverse effects such as increased fuel consumption, pollution, noise, and road accidents are inevitable. One of the most efficient ways to mitigate congestion-related adverse effects is to introduce effective intelligent transportation systems (ITS), using advanced technologies and mobile communication protocols to make roads smarter and reduce negative impacts such as improvement in fuel consumption and pollution, and reduction of road accidents, which leads to improving quality of life. Smart roads might play a growing role in the improved safety of road transportation networks. This study aims to evaluate and rank the potential smartification measures for the road network in Calabria, in southern Italy, with sustainable development goals. For this purpose, some potential smartification measures were selected. Experts in the field were consulted using an advanced procedure: four criteria were considered for evaluating these smartification measures. The Integrated fuzzy decision support system (FDSS), namely the fuzzy Delphi analytic hierarchy process (FDAHP) with the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) were used for evaluating and ranking the potential smartification measures. The results demonstrated that the repetition of signals in the vehicle has the highest rank, and photovoltaic systems spread along the road axis has the lowest rank to use as smartification measures in the roads of the case study.

Occupational Risk Assessment of Wind Turbines in Bangladesh

Wind energy is among the foremost vital renewable energy sources in the world. With the increase in its popularity and use, the requirement for safety measures regarding this type of energy is becoming more prevalent. The development and operation requirements that come with installing and running wind turbines have many risks that need managing and mitigation. This study implemented a risk evaluation method for the transportation, construction, operation, and maintenance of wind turbines, employing the fuzzy method. Fuzzy Analytical Hierarchy Process (FAHP), a multi-criteria higher cognitive process technique, was used to determine the weights of the risk parameters evaluated with the Fine–Kinney method. After that, the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) was employed for ranking the hazard’s source. Using Occupational Health and Safety (OHS) consultants, this study was conducted in Bangladesh regarding its onshore turbines. Findings have revealed that the most prevalent hazards during transportation, construction, operation, and maintenance, respectively, are “Driving vehicles at night in dark weather conditions”, “Work in hot and humid conditions”, “Inclement weather”, and “Entering of unauthorized persons”. The results of this study can help the OHS department to track these risks and to control and minimize them.

Location of Emergency Escape Ramps on Two-Lane Rural Highways Based on the Fuzzy Multicriteria Decision-Making Method

Today, the lack of practical research is one of the most important concerns worldwide, and location, which is an important issue in most projects, has received less attention from experts. In this study, the location criteria of emergency escape ramps were examined, and according to the Myers formula, the temperature-distance diagram along the route was obtained. Also, the speed of vehicles entering the escape ramp was examined according to the American Association of State Highway and Transportation Officials (AASHTO) in the proposed options that were obtained from the experts. Then, 3 general criteria and 16 subcriteria were classified, and finally, the importance of criteria was examined by the fuzzy analytic hierarchy process (F-AHP), and the high-priority options were illustrated using the fuzzy technique for order performance by similarity to ideal solution (F-TOPSIS). The proposed options were evaluated and prioritized for an emergency escape ramp on the two-lane rural highways of Salavat Abad village pass of Sanandaj city, Kurdistan Province, Iran. The results showed that the technical criteria with more than 69% among the general criteria and subcriteria of the percentage of longitudinal slope, longitudinal slope length, and vehicle design speed were the most important factors influencing the location of an emergency escape ramp. Moreover, among the proposed options, the four options 3, 4, 5, and 6 had the highest score, and option 6 (Kurkur turn (2)) was identified as the most priority location for implementing the emergency escape ramp.

Quantitative Evaluation of Mental-Health in Type-2 Diabetes Patients Through Computational Model

A large number of people live in diabetes worldwide. Type-2 Diabetes (D2) accounts for 92% of patients with D2 and puts a huge burden on the healthcare industry. This multi-criterion medical research is based on the data collected from the hospitals of Uttar Pradesh, India. In recent times there is a need for a web-based electronic system to determine the impact of mental health in D2 patients. This study will examine the impact assessment in D2 patients. This paper used the integrated methodology of Fuzzy Analytic Hierarchy (FAHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS). The FAHP determines the impact of factors, which is classified by two levels. The first levels have three factors; Body Mass Index (BMI), Systolic Blood Pressure (SBP), and Diastolic Blood Pressure (DBP). The second level, selects the factors-age, weight, height, exercise (50 to 70 min), and mental health. Furthermore, the alternatives are hospitals A1 to A6. The authors gather the data from the hospitals in different places of state Uttar Pradesh, India. The FTOPSIS approach determines the rank of alternatives. The integrated model shows the applicability and impact of data on mental health in D2 patients. This study explains the complexity of the D2 patient's condition. The multi-criterion medical research is compared with some existing methods, which confirms the strength and stability of the proposed FAHP and FTOPSIS methodology.

Mathematical modeling and evaluation of the safety culture for the operating nuclear power plants in China: Critical review and multi-criteria decision analysis

The health and safety of an operating nuclear power plant (NPP/ONPP) is its important objective and task, which is usually accomplished by strengthening nuclear safety culture (NSC). With the objective to establishing an effective system of NSC assessment (NSCA) index, the present paper adopts the method of multiple criteria decision analysis (MCDA) and constructs a NSCA model in order to rank the NSC level of different job positions. It first of all applies a combination of fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and fuzzy network analytic process (FNAP) to determine the weights of the different indexes of the NSC, on the basis of which the NSC level of the selected seven job positions of an ONPP is ranked by employing the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method. The results thus obtained demonstrate that the safety culture level of general manager was the highest, whereas that level of field operator was the lowest. In addition, it was necessary to systematically strengthen employee responsibility awareness and scientific management decision-making process. In brief, the present research and procedure could facilitate the establishment of a healthy safety culture, and effectively improve organizational safety culture and become a bulwark against safety accidents in the ONPP.

Decision model using hierarchical fuzzy TOPSIS: Towards improving decision making in food waste management

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is based on decision model to measure alternative with shortest distance to positive ideal solution and the farthest distance from negative ideal solution. With growing complexity in decision making, vagueness and uncertainty often exist in human judgement. To manage conflicting criteria, a hierarchy structure in TOPSIS is proposed where the main criteria, sub-criteria, and alternatives are arranged in multi-level. To rate each alternatives, the weight of each criterion is evaluated using linguistic value before converted into fuzzy number as a way to measure the experts opinion. In this paper, we demonstrates our general framework for the development of hierarchal fuzzy TOPSIS. We also highlighted our initial finding on the criteria and alternatives in our case study i.e. selection of decomposition technology for food waste management. It is anticipates our work will contributes better decision making in the related area.