Technique For Order Preference By Similarity To Ideal Solution Methodology Research Articles

Selection of 3D Printer for Innovation Centre of Academic Institution Based on AHP and TOPSIS Methods

Abstract: This paper describes a computer-based tool for the selection of 3D printer for educational propose by using Multi Attribute Decision Making (MADM) strategies particularly Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In education, 3D printing technologies facilitate improved learning, skills development, and increased student and teacher engagement with the subject matter. Furthermore, 3D printing sparks greater creativity and collaboration in solving problems, to settle on a best option for teaching learning process tasks into account. MADM methods are interpretative processes which are well suited in choice of different 3D printers. This work suggests AHP and TOPSIS to judge 3D printer alternatives for choice of method, based on the AHP and TOPSIS methodology, ranks available techniques by a score resulting from the composition of priorities at different levels, each considering homogeneous and independent evaluation criteria. In this work proposes a comprehensive list of key factors that have a significant influence on 3D printer selection. In this work type of material used for printing considered as common for all printers such as ABS (Acrylonitrile Butadiene Styrene), PLA (Polylactic Acid), PET or Polyethylene terephthalate etc. A total of 09 sub-criteria have been identified and grouped under three main criteria, namely, (i) Physical Characteristics (ii) Economic consideration, (iii) Operational Requirements. These entire criteria area unit extracted from on-line literature and skilled opinion. Result of study shows that 3D Printer one (ET4 PRO 3IDEA model) was designated because the best suited for Innovation Centre Academic Institution. Keywords: 3D printer, MADM method, AHP method, TOPSIS method, Innovation Centre, Academic Institution

Selection of phase change material for improved performance of Trombe wall systems using the entropy weight and TOPSIS methodology

The past decade has witnessed a lot of technological advancement towards the use of renewable and sustainable energy resources, these efforts are geared towards mitigating the effect of climate change and to make our environment safe and habitable. Today, buildings account for over 40% of the world's total energy consumption. Thermal energy storage in buildings contributes significantly to the reduction of building energy demand by releasing its stored energy when the demand arises. Trombe walls are used for thermal energy storage and delivery in buildings and thus regulates the rooms ambient temperature. A lot of studies have considered the use of phase change materials for latent heat thermal energy storage in Trombe walls in order to improve its performance. The selection of phase change materials for optimum Trombe wall performance was considered in this article, the weights of the various criteria were determined using the entropy weight method while the various alternative phase change materials were ranked using the technique for order preference by similarity to ideal solution (TOPSIS) methodology. The four criteria considered were the heat of fusion, thermal conductivity, density, and cost. A total of eleven commonly available phase change materials were considered in this study, with phase change temperatures within the range 18 C–28 C which corresponds to the average temperature range for human comfort. The result had the thermal conductivity was assigned the highest weight of 72.12% while the eutectic combination of capric acid and palmitic acid ranked the best at 95.1% for Trombe wall application.

Efficient supplier selection - a three-stage multi-criteria decision-making approach

The qualitative and quantitative factors influence the supplier selection problem. The selection of an efficient supplier is a difficult task and is a multi-criteria decision-making problem. In the present study, a three-stage analytic hierarchy process (AHP)-technique for order preference by similarity to ideal solution (TOPSIS)-goal programming (GP) was employed for the evaluation and selection of suppliers. AHP was used for identifying relative weight of the selection criteria then these weights were taken as input for TOPSIS methodology for ranking the shortlisted suppliers. GP was used for the quantity allocation. This study is intended to guide the organisational managers in formulating the effective policies and strategies for the effective supplier selection process in the competitive environment.

Prioritization of production strategies of a manufacturing plant by using an integrated intuitionistic fuzzy AHP & TOPSIS approach

PurposeThe purpose of this paper is to find most appropriate production strategy for a manufacturing plant by using an integrated interval-valued intuitionistic fuzzy (IVIF) analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach.Design/methodology/approachThe applied methodology is a multi-criteria decision making approach consists of AHP and TOPSIS methods with the extension of intuitionistic fuzzy sets.FindingsResults of the application are revealed that using integrated IVIF-AHP & TOPSIS methods are very appropriate for the prioritization of the strategy for the production management for a manufacturing plant. This outcome also is supported by the sensitivity analysis. Results of the sensitivity analysis demonstrate the robustness of the methodology.Originality/valueTo the best of the authors’ knowledge, an integrated IVIF-AHP & TOPSIS methodology is used for the prioritization of production strategies for the first time.

A hybrid decision support model using axiomatic fuzzy set theory in AHP and TOPSIS for multicriteria route selection

This paper presents a hybrid decision support model aimed to help the travelers in selecting best route among multiple alternatives. The proposed model consists of three parts: (i) analytic hierarchy process (AHP) to determine relative importance of route attributes, (ii) axiomatic fuzzy set (AFS) theory for description of alternative routes, and (iii) technique for order preference by similarity to ideal solution (TOPSIS)-based final selection. TOPSIS methodology is used to determine ranking order of alternative routes in multicriteria decision situations. In TOPSIS, the alternative routes are described using AFS theory to normalize the decision matrix for consistent rating of routes over attributes. The main advantage of the developed model is that it copes inconsistency caused by both, different types of fuzzy numbers and normalization methods. An illustrative example of route selection is presented to better understand the hybrid methodological process. A comparative analysis with an established multicriteria decision-making technique shows the effectiveness and validity of the hybrid model for route selection.

3PL provider selection by AHP and TOPSIS methodology

PurposeThe purpose of this paper is to provide a two-phase analytical hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) approach that is a multi-criteria decision-making methodology (MCDM) in the evaluation of third-party logistics (3PL) providers.Design/methodology/approachAfter the description of the selection criteria of 3PL providers that are determined by company management, the weights of criteria are calculated by applying the AHP method. The TOPSIS method is then employed to achieve the final ranking results. A sensitivity analysis is developed for a deeper comprehension of results reliability.FindingsThe paper shows the complexity of a real 3PL provider change. At the same time, a simple MCDM methodology is provided to assure the success of this activity in which many other companies have failed.Research limitations/implicationsThe proposed MCDM methodology represents a very good compromise between a reliable solution and reasonable computational and human effort. 3PL provider selection or change is an extremely complex decision that could be investigated in greater detail with other more complex methodology, with a consequently higher investment, that is not so affordable for all budgets.Originality/valueIt is the first time that a two-phase AHP and TOPSIS methodology is applied to an Italian biscuit company for a 3PL provider change together with the analysis of logistics performance after two years. The paper shows a detailed methodology application that could be very useful for managers for their specific application.

Integrated Fuzzy Technique for Order Preference by Similarity to Ideal Solution Framework for Evaluating High-Speed Passenger Rail Corridor Alternatives

This paper develops a multiple criteria and multimethod approach for evaluating the suitability of alternative right-of-way (ROW) corridors to accommodate high-speed intercity passenger rail (HSIPR) operations. An alignment decision for HSIPR involves consideration of multiple criteria and trade-offs. Policy makers often face uncertainty in evaluating and selecting alternative options and usually consider alternatives in a fuzzy environment in which subjectivity and vagueness are present. This paper develops an integrated evaluation model that uses the fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods to address some of these issues. The study identifies potential sketch-planning performance metrics and demonstrates their usefulness and inclusion in the integrated fuzzy AHP–TOPSIS methodology in comparing alternative ROW corridor options. In contrast to detailed engineering evaluation, the developed sketch-planning metrics provide a cost- and time-effective way of assessing alternative suitability. A case study application with existing highway ROW in Texas demonstrates the applicability of the proposed framework. Apart from ranking alternatives, a detailed sensitivity analysis assesses the effect of performance metrics weights on the preferences between alternatives using a displacement index. The proposed framework creates a more effective and systematic decision support tool for preliminary corridor alternative evaluation.

Evaluation of Lean Manufacturing Systems Using MADM and Fuzzy TOPSIS

Lean manufacturing is a management philosophy derived from Toyota Production System (TPS) which aims to increase the overall values of the product or service provided to the customer through elimination of non-value added activities. In the era of globalisation, to remain competitive in the global market, many medium and small sized Indian industries adopt lean manufacturing. This paper focuses on implementation of lean manufacturing in Indian MSMEs. To examine the implementation, attributes which influence lean manufacturing are obtained and industries’ performances on these criteria are rated. In this paper, the methodology selected from many of the multi criteria models is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In the actual real world situation, because of the unreliable nature of the information gathered, the attributes are often not absolute and are imprecise. These data can be considered as fuzzy and the aim of this paper is to adopt TOPSIS decision making method to problems with fuzzy data. The rating and weights of each data are expressed as triangular fuzzy numbers. These attributes are then normalized and the TOPSIS methodology is carried out to determine the effect of implementing lean manufacturing technique in an industry. The best industry is identified by fuzzy TOPSIS on the basis of performance towards the considered attributes is consistent with results identified by TOPSIS.

Hierarchical multi-criteria risk-benefit analysis in fuzzy environment

The objectives of this paper are: (1) to utilize hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to evaluate the most suitable RFID-based systems decision and (2) to list key risks and benefits of radio frequency identification technology in library services. Researcher explains the importance of selection criteria for evaluation of RFID-based systems. It provides key elements on radio frequency identification, fuzzy hierarchical TOPSIS methodology and an algorithm that can be followed to solve the problem. A sample problem using the algorithm is solved and results are explained. Due to the fact that a better management of a library system is related to the full understanding of the technologies implemented and the system under consideration, some background on the radio frequency identification technology is provided and the kind of systems that most likely managements would face with and select are provided.

Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.

Selection of logistics center location using Axiomatic Fuzzy Set and TOPSIS methodology in logistics management

This article presents a comprehensive methodology for the selection of logistic center location. The proposed methodology consists of two parts: (i) AFS (Axiomatic Fuzzy Set) clustering method (Liu, Wang, & Chai, 2005) has been studied further to effectively evaluate logistics center location, and (ii) TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)-based final selection. The criteria, which are relevant in the selection of logistics center site, have been analyzed and identified, and the logistics center site evaluation system is built by using modern principles of town planning and logistics. A case fifteen regional logistics center cities and thirteen criteria are studied and the numerical results show that the proposed evaluation framework is reasonable to identify logistics center location, and it is effective to determine the optimal logistics center location even with the interactive and interdependent criteria/attributes.

Evaluation of third‐party logistics (3PL) providers by using a two‐phase AHP and TOPSIS methodology

PurposeThird‐party logistics (3PL) provider selection has gained great attention in logistics management literature. The purpose of this paper is to provide a good insight into the use of a‐two‐phase analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach that is a multi‐criteria decision‐making methodology in the evaluation of 3PL providers.Design/methodology/approachIn this paper, after the selection criteria of 3PL providers are determined by modified Delphi method, the weights of criteria have been calculated by applying the AHP method. The TOPSIS method is then employed to achieve the final ranking results. And an actual case example is presented to clarify the methodology. Sensitivity analysis is also given to demonstrate how sensitive the proposed model is to changes in the weights of different main criteria.FindingsThis model provides decision makers with a simple, flexible, and easy‐to‐use approach to evaluate potential 3PL providers efficiently. Findings demonstrate that the proposed benchmarking framework, with minor modifications, can be useful to all firms in their 3PL provider selection decisions.Research limitations/implicationsA two‐phase AHP and TOPSIS methodology is very flexible and suitable for various decision situations. However, selection of the appropriate 3PL provider requires consideration of multiple alternative solutions and evaluation criteria because of complex methodology, and hence it increases the effort.Originality/valueThis is probably the first time that an attempt has been made to apply the modified Delphi method, AHP and TOPSIS methodology in the decision of 3PL provider selection in a Turkish automotive supplier company. This is the most powerful motivation to consider this problem. In addition, the paper is especially of interest to managers as they make decisions on which criteria should be considered in the evaluation process and how a decision model should be structured by using a two‐phase AHP and TOPSIS methodology.