An integrated fuzzy approach for classifying slow-moving items

2018 ◽  
Vol 31 (4) ◽  
pp. 595-611 ◽  
Author(s):  
Irem Otay ◽  
Embiye Senturk ◽  
Ferhan Çebi
Keyword(s):  
Fuzzy Ahp ◽  
Real Life ◽  
Integrated Approach ◽  
Classification Problem ◽  
Ahp Method ◽  
Content Type ◽  
Integrated Method ◽  
Slow Moving ◽  
Abc Analysis ◽  
Interval Type

Purpose The purpose of this paper is to propose a new integrated method for evaluating inventory of slow-moving items by introducing the application of fuzzy AHP method with interval Type-2 fuzzy sets (IT2FSs) and ABC analysis. Design/methodology/approach In the study, fuzzy analytic hierarchy process (AHP) method with IT2FSs is employed to set the importance of criteria. The weights obtained from IT2 fuzzy AHP are used to classify slow-moving items in ABC analysis. In the application part, a real-life case study is presented. Findings The result of this study indicates that an integrated approach utilizing IT2 fuzzy AHP and ABC analysis can be used as a supportive tool for classification of slow-moving items. The problem is solved under fuzzy environment to handle uncertainties and lack of information about slow-moving items. Practical implications Actual data are provided from an automotive company for prioritizing a various criteria to evaluate and classify stocks and a hypothetical model integrated with IT2 fuzzy AHP and ABC analysis is demonstrated. Originality/value Apart from inventory classification literature, the study integrates fuzzy AHP method by employing interval IT2FSs and ABC analysis to solve the real-life inventory classification problem.

Interval type-2 fuzzy inference-based failure mode and effect analysis model in a group decision-making setting

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
İlker Gölcük
Keyword(s):  
Failure Modes ◽  
Fuzzy Inference ◽  
Real Life ◽  
Effect Analysis ◽  
Inference System ◽  
Content Type ◽  
Proposed Model ◽  
Interval Type

PurposeThis paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.Design/methodology/approachThis paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.FindingsThe proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.Originality/valueMamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

The multi resource leveling and materials procurement problem: an integrated approach

2020 ◽  
Vol 27 (9) ◽  
pp. 2135-2161
Author(s):  
Hessa Almatroushi ◽  
Moncer Hariga ◽  
Rami As'ad ◽  
AbdulRahman Al-Bar
Keyword(s):  
Renewable Resources ◽  
Project Scheduling ◽  
Lot Sizing ◽  
Real Life ◽  
Integrated Approach ◽  
Project Schedule ◽  
Sequential Approach ◽  
Content Type ◽  
Ordering Policy ◽  
Solution Methods

PurposeThis paper proposes an integrated approach that seeks to jointly optimize project scheduling and material lot sizing decisions for time-constrained project scheduling problems.Design/methodology/approachA mixed integer linear programming model is devised, which utilizes the splitting of noncritical activities as a mean toward leveling the renewable resources. The developed model minimizes renewable resources leveling costs along with consumable resources related costs, and it is solved using IBM ILOG CPLEX optimization package. A hybrid metaheuristic procedure is also proposed to efficiently solve the model for larger projects with complex networks structure.FindingsThe results confirmed the significance of the integrated approach as both the project schedule and the material ordering policy turned out to be different once compared to the sequential approach under same parameter settings. Furthermore, the integrated approach resulted in substantial total costs reduction for low values of the acquiring and releasing costs of the renewable resources. Computational experiments conducted over 240 test instances of various sizes, and complexities illustrate the efficiency of the proposed metaheuristic approach as it yields solutions that are on average 1.14% away from the optimal ones.Practical implicationsThis work highlights the necessity of having project managers address project scheduling and materials lot sizing decisions concurrently, rather than sequentially, to better level resources and minimize materials related costs. Significant cost savings were generated through the developed model despite the use of a small-scale example which illustrates the great potential that the integrated approach has in real life projects. For real life projects with complex network topology, practitioners are advised to make use of the developed metaheuristic procedure due to its superior time efficiency as compared to exact solution methods.Originality/valueThe sequential approach, wherein a project schedule is established first followed by allocating the needed resources, is proven to yield a nonoptimized project schedule and materials ordering policy, leading to an increase in the project's total cost. The integrated approach proposed hereafter optimizes both decisions at once ensuring the timely completion of the project at the least possible cost. The proposed metaheuristic approach provides a viable alternative to exact solution methods especially for larger projects.

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

A fuzzy AHP and TOPSIS methodology to evaluate 3PL in a supply chain

2012 ◽  
Vol 7 (3) ◽  
pp. 287-303 ◽  
Author(s):  
Pravin Kumar ◽  
Rajesh K. Singh
Keyword(s):  
Supply Chain ◽  
Service Providers ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Third Party ◽  
Preference Ranking ◽  
Relative Importance ◽  
Content Type ◽  
Logistics Service Providers ◽  
Hierarchy Process

PurposeThe purpose of this paper is to provide an insight into the use of an integrated approach of fuzzy analytical hierarchy process (fuzzy AHP) and TOPSIS in evaluating the performance of global third party logistics service providers for effective supply chain management.Design/methodology/approachIn this study, the integration of fuzzy AHP with TOPSIS is proposed in determining the relative importance (weight) of criteria and then ranking of 3PLs.FindingsFindings show that the logistics cost and service quality are two most important criteria for performance rating of 3PLs. Deciding the relative importance of various criteria for 3PLs evaluation is a complex task. The superiority of one criterion over the other varies from person to person and firm to firm. Therefore, to capture the variability in decision fuzzy extended AHP is very useful tool. Finally, the preference raking of alternatives are found using TOPSIS.Research limitations/implicationsFuzzy AHP is a complex methodology and requires more numerical calculations than the traditional AHP and hence it increases the effort. But in this paper single stage fuzzy AHP is used to simplify the process. Fuzzy AHP is integrated with TOPSIS for preference ranking of 3PL, which provides a good methodology to rank 3PLs.Originality/valueThere is a lack of research in the literature to deal directly with the uncertainty of human decisions in evaluating the relative importance of multiple criteria. Therefore, fuzzy AHP is an appropriate methodology to find the relative importance of the criteria to rank the 3PLs using TOPSIS.

An integrated DEA-based approach for evaluating and sizing health care supply chains

2019 ◽  
Vol 15 (1) ◽  
pp. 201-231
Author(s):  
Zoubida Chorfi ◽  
Abdelaziz Berrado ◽  
Loubna Benabbou
Keyword(s):  
Health Care ◽  
Supply Chains ◽  
Real Life ◽  
Integrated Approach ◽  
Interval Data ◽  
Pharmaceutical Supply Chain ◽  
Content Type ◽  
Integrated Methodology ◽  
Dea Models ◽  
Health Care Supply

Purpose Evaluating the performance of supply chains is a convoluted task because of the complexity that is inextricably linked to the structure of the aforesaid chains. Therefore, the purpose of this paper is to present an integrated approach for evaluating and sizing real-life health-care supply chains in the presence of interval data. Design/methodology/approach To achieve the objective, this paper illustrates an approach called Latin hypercube sampling by replacement (LHSR) to identify a set of precise data from the interval data; then the standard data envelopment analysis (DEA) models can be used to assess the relative efficiencies of the supply chains under evaluation. A certain level of data aggregation is suggested to improve the discriminatory power of the DEA models and an experimental design is conducted to size the supply chains under assessment. Findings The newly developed integrated methodology assists the decision-makers (DMs) in comparing their real-life supply chains against peers and sizing their resources to achieve a certain level of production. Practical implications The proposed integrated DEA-based approach has been successfully implemented to suggest an appropriate structure to the actual public pharmaceutical supply chain in Morocco. Originality/value The originality of the proposed approach comes from the development of an integrated methodology to evaluate and size real-life health-care supply chains while taking into account interval data. This developed integrated technique certainly adds value to the health-care DMs for modelling their supply chains in today's world.

Supply chain performance measurement for third party logistics

2014 ◽  
Vol 21 (6) ◽  
pp. 944-963 ◽  
Author(s):  
Dhanya Jothimani ◽  
S.P. Sarmah
Keyword(s):  
Supply Chain ◽  
Performance Measurement ◽  
Asset Management ◽  
Real Life ◽  
Integrated Approach ◽  
Third Party ◽  
Supply Chain Performance ◽  
Third Party Logistics ◽  
Content Type ◽  
Scor Model

Purpose – The purpose of the paper is to explore the applicability of the Supply Chain Operations Reference (SCOR) model and to identify the key performance indicators (KPIs) for the service-oriented sector – namely a third-party logistics (3PL) service provider. Design/methodology/approach – The performance attributes of SCOR model (reliability, responsiveness, flexibility, cost measures and asset management efficiency) are used as the basis for defining the KPIs. A questionnaire was sent to relevant decision makers. Findings – This paper illustrates the use of the integrated approach of SCOR, fuzzy analytic hierarchy process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for measuring the supply chain performance (SCP) in the light of a real life case study company. Research limitations/implications – This method forms the basis for performance measurement using the SCOR model to evaluate strategy. In this work, the performance of the company has been compared with its own previous performance. The work can be extended to external benchmarking and also to other sectors. Practical implications – The paper attempts to overcome the conflict between the top-down strategy and bottom-up implementation process. The paper links the strategic objective with operations which would aid managers at different levels of an organization with decision making. The KPIs, when implemented in a business intelligence (BI) tool, would result in real time performance measurement. Originality/value – The paper focusses on 3PLs. It provides a base for measuring the SCP using SCOR model. The paper also identified KPIs for three domains of 3PL, namely freight forwarding, customs and warehousing.

A fuzzy MCDM algorithm and practical decision aid tool to determine the best ROV design alternative

Kybernetes ◽  
2015 ◽  
Vol 44 (4) ◽  
pp. 623-645 ◽  
Author(s):  
Birol Ülker
Keyword(s):  
Sensitivity Analysis ◽  
Decision Process ◽  
Decision Aid ◽  
Fuzzy Ahp ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Manufacturing Companies ◽  
Remotely Operated Vehicle ◽  
Content Type ◽  
Design Alternative

Purpose – Proposing a fuzzy multi-criteria decision making (MCDM) algorithm that is able to incorporate the heterogeneousness effect of DM group into the decision process, in order to determine the best remotely operated vehicle (ROV) design alternative to manufacture and developing a practical decision aid tool based on this algorithm. The paper aims to discuss these issues. Design/methodology/approach – An algorithm utilizes fuzzy AHP Buckley’s approach for modeling heterogeneousness of the DM group, fuzzy AHP Chang’s extent analysis to calculate the priority values of criteria and Chen’s fuzzy TOPSIS for ranking the alternatives and finally group working technique for initiation issues is developed. MATLAB is used to implement the algorithm and generate a decision aid tool. Real life application and sensitivity analysis is performed by the help of generated tool. Literature and background explanations are also provided. Findings – A MCDM algorithm that incorporates the heterogeneousness effect of the DM group into the decision process is introduced. Sensitivity analysis suggested the independence of the final result from DM group and criteria set. A practical decision aid tool is generated for ROV manufacturing companies. Practical implications – A computerized MCDM aid tool that incorporates heterogeneousness of the DM group into the decision process is generated. Tool let ROV manufacturing companies to evaluate ROV design alternatives with respect to qualitative and quantitative criteria and determine proper choice. Originality/value – Determination of the proper ROV design alternative to manufacture gap within the literature filled with an algorithm that provides more reliable results due to its incorporation the heterogeneousness of the DM group into the decision process characteristic. A practical decision aid tool is generated.

An integrated fuzzy-AHP and TOPSIS approach for maintenance policy selection

2019 ◽  
Vol 37 (9/10) ◽  
pp. 1275-1299 ◽  
Author(s):  
Narges Hemmati ◽  
Masoud Rahiminezhad Galankashi ◽  
D.M. Imani ◽  
Farimah Mokhatab Rafiei
Keyword(s):  
Heat Exchanger ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Added Value ◽  
Risk Level ◽  
Maintenance Policy ◽  
Content Type ◽  
Policy Selection ◽  
Different Types ◽  
Molten Sulfur

Purpose The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models. Design/methodology/approach The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies. Findings The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace. Originality/value This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.

The role of 3S in big data quality: a perspective on operational performance indicators using an integrated approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pratima Verma ◽  
Vimal Kumar ◽  
Ankesh Mittal ◽  
Bhawana Rathore ◽  
Ajay Jha ◽  
...  
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Data Science ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Preference Ranking ◽  
Content Type ◽  
Quality Dimensions ◽  
Data Quality Dimensions

PurposeThis study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.Design/methodology/approachA fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.FindingsThe effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.Research limitations/implicationsThe outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.Originality/valueBig data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.

Fuzzy AHP-GRA approach to evaluating energy sources: a case of Turkey

2020 ◽  
Vol 14 (1) ◽  
pp. 40-58 ◽  
Author(s):  
Zeki Ayağ ◽  
Funda Samanlioglu
Keyword(s):  
Energy Source ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Integrated Approach ◽  
The Other ◽  
Energy Sources ◽  
Public And Private ◽  
Content Type ◽  
Other Hand ◽  
Fuzzy Gra

Purpose Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey. Design/methodology/approach In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA. Findings The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management. Research limitations/implications In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives. Practical implications In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors. Social implications On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world. Originality/value On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem.

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