Interval TOPSIS Research Articles

Hybrid MCDM and simulation-optimization for strategic supplier selection

Supplier selection for strategic items requires a comprehensive framework dealing with qualitative and quantitative aspects of a company’s competitive priorities and supply risk, decision scope, and uncertainty. In order to address these aspects, this study aims to tackle supplier selection for strategic items with a multi-sourcing, taking into account multi-criteria, incorporating uncertainty of decision-makers judgment and supplier–buyer parameters, and integrating with inventory management which the past studies have not addressed well. We develop a novel two-phase solution approach based on integrated multi-criteria decision-making (MCDM) and multi-objective simulation-optimization (S-O). First, MCDM methods, including fuzzy AHP and interval TOPSIS, are applied to calculate suppliers’ scores, incorporating uncertain decision makers’ judgment. S-O then combines the (quantitative) cost-related criteria and considers supply disruptions and uncertain supplier–buyer parameters. By running this approach on data generated based on previous studies, we evaluate the impact of the decision maker’s and the objective’s weight, which are considered important in supplier selection.

Two-Level Assessment Method for Electrical Fire Risk of High-Rise Buildings based on Interval TOPSIS Method

Two-Level Assessment Method for Electrical Fire Risk of High-Rise Buildings based on Interval TOPSIS Method

Furniture material selection for hotel and airlines lounges using interval TOPSIS

The interior design of hotel inevitably includes the furniture installation. The design of furniture needs to select suitable material. Modern material production provides numerous alternatives but at the same time create another problem of selection the suitable one. The properties of materials in different aspects, e.g. strength, style, durability, etc., form a set of criteria in the selection. The criteria are normally conflicting and pose difficulty in the selection process. This paper proposes an MCDM methodology, namely interval TOPSIS, to facilitate the selection process by ranking the prospect materials according to a set of criteria. The interval TOPSIS is suitable for the real-world application where there is uncertainty in terms of interval numbers. The methodology is illustrated through an illustrative example. The methodology is readily extended to the material selection in other domain of application.

How to handling with uncertain data in the TOPSIS technique?

Abstract The methods of multi-criteria decision making are more and more willingly used as assistance in finding an optimal solution to the problem. As the family of these methods grows, choosing the appropriate technique and whether the use of multiple methods for one problem will provide a similar final result may be a problem. In this paper, extensions of the classic TOPSIS method have been used to show one decision problem results. We used the Interval TOPSIS, Bag-Based TOPSIS, and Fuzzy TOPSIS methods to examine the influence of used methods to final rankings. They solved the theoretical problem of selecting a high-protein supplement for persons in power training. The results were then compared using selected similarity coefficients to emphasize the correlation between the resulting rankings. The research showed that the method used has an impact on the final ranking, which was confirmed by the indicators obtained through the similarity coefficients.

An integrated MILP-MCDM decision framework for uncertain multi-criteria facilities location problem of glass industries

In existence of interval-valued parameters and managerial limitations, MCDM problems become more complex than their classical versions. In such cases, the classical MCDM techniques are not quite useful solution tools. This study focuses on a MCDM problem to establish the branches of a glass production company in all districts of Iran in existence of interval-valued parameters and managerial limitations. To overcome the above-mentioned difficulties, a typical decision framework is proposed. In the proposed framework, first, an interval Shannon's entropy approach is proposed to find interval criteria weights. Then a full interval TOPSIS approach is proposed to score the potential locations. Finally, using the obtained scores, a mixed integer linear programming model is developed to respect the constraints and find an optimised set of potential locations for the new branches. The proposed decision framework is validated by the real data of the case study and its sensitivity is studied in detail.

Two-step procedure for multi-criteria choice of generating-capacity structure in remote areas

The paper dwells upon the problem of multi-criteria choice of ways to develop generating capacities to supply power to remote consumers. We herein propose a two-step multi-criteria analysis method: choosing promising power-generation technology first, and then specifying the generating-capacity structure. The paper describes the structure of the proposed multi-criteria methods: the interval TOPSIS method for Step 1; for Step 2, an upgraded analytic hierarchy process based on identifying the structure of the decision maker’s preferences. We demonstrate the use of this method with evidence from the Penzhinsky District, Kamchatka Krai. Thermal power plants, hydroelectric power plants, diesel power plants, as well as solar and wind power are analyzed as power sources. Step 1 includes: analyzing the potential power-supply loads in a specific area; formulating alternative power-generation technology; formulating goals and criteria; criterion-based evaluation of alternative options using objective and subjective models; multi-criteria evaluation of alternatives; analyzing the sensitivity of results and the selection of promising technology. Step 2 includes: formulating goals and criteria on the basis of the selected power-generation technologies; formulating the available alternatives; criterion-based evaluation of alternatives; multi-criteria evaluation and final decision-making.

Multi-criteria supplier evaluation/selection by considering ethical factors under uncertainty

In recent years, companies pay more attention to ethic and ethical issues have become a key determinant of performance in the business arena. This is not an area which has been systematically examined. From the literature, it appears to be assumed that the supplier selection is multiple attribute decision making/multiple criteria decision making (MADM/MCDM) problem, information and performances usually incomplete and uncertain, and supplier ethics is becoming another key factor to consider, too. The question typically posed is; how ethical factor can be modelled formally for an established MCDM models? In this paper, we propose a new interval TOPSIS-based procedure to resolve this problem. So, the proposed method has a capability to identify a measure of unethical performance with input and output system balancing, and consist of the two-step. In the first step, a new interval TOPSIS-based approach is used, results of this step are input for conventional interval TOPSIS method in the second step. The results indicate that the accuracy of the decision has been increased by considering the ethical factors.

Multi-criteria decision making for the prioritization of energy systems under uncertainties after life cycle sustainability assessment

This study aims at developing a life cycle sustainability prioritization framework for ranking the energy systems under uncertainties. The fuzzy two-stage logarithmic goal programming method was firstly employed to determine the weights of the criteria for sustainability assessment, and the interval grey relational analysis method was subsequently used to determine the sustainability order of the alternative energy systems. Then, an illustrative case including four alternatives for electricity generation in UK, namely, coal-pulverized, combined cycle gas turbines, nuclear-pressurized water reactor, and offshore wind powder based electricity, was investigated, and pressurized water reactor was recognized as the most sustainable, followed by combined cycle gas turbines, offshore wind powder, and coal-pulverized in the descending order. Finally, the results were validated by the interval TOPSIS, and sensitivity analysis was also carried used to investigate the effects of the weights of the criteria for sustainability assessment on the final sustainability order of the alternative energy systems.

Polygeneration system and sustainability: Multi-attribute decision-support framework for comprehensive assessment under uncertainties

As an important energy-efficient production technology, polygeneration has attracted more and more attentions for its advantages of high energy efficiency, low production cost, and fewer emissions compared with the traditional industrial systems. The objective of this study is to develop a multi-attribute comprehensive assessment method for sustainability assessment of polygenerations under uncertainty conditions. Fuzzy best-worst network method which can incorporate the interdependences and interactions among the evaluation criteria has been developed for determining the weights of the criteria. Interval TOPSIS which can rank the alternative under uncertainties has been employed to rank the alternative polygeneration systems according to their sustainability performance. In order to illustrate the proposed method, an illustrative case including four industrial systems has been studied, and the results were also validated by interval grey relational analysis (GRA) method. Sensitivity analysis was also carried out to investigate the effects of the weights of the criteria on the sustainability ranking of the four polygeneration systems.

An Integrated Product Design and Selection Approach Using Grey QFD and Grey TOPSIS Methods

Quality function deployment (QFD) is a successful product design tool for analyzing customer demands. Recently, researchers have combined QFD and grey system theory for solving small size, uncertain and incomplete data problems. However, some problems, such as single grey values, competitive analysis and prototype product selections, require further investigation. To resolve these issues, this study integrates interval grey numbers, QFD and TOPSIS techniques to develop a grey product design and selection (GPDS) method. GPDS can help product developers identify important engineering characteristics, perform a competitive analysis and select the best prototype product(s) under a small size and uncertain data environment. A real-world case study (paper facial mask) is offered to explain the research process of the GPDS method. The case results indicate that GPDS helps the case company identify important engineering characteristics, understand the intended market position of a product and select the best prototype product.

Evaluation of Knowledge Absorptive Capability of Enterprise Based on Entropy Weights and Interval TOPSIS

The processes for absorbing knowledge become an essential element for innovation and competitiveness in enterprises. Despite the huge growth in the absorptive capacity literature, a method gap still remains about a certain ambiguity in the measurement of the construct specifying its theoretical domain. The aim of this paper is to contribute to the research on absorptive capacity through the construction of four aspects, based on a thorough analysis of the literature and field research, to measure the key components of the absorptive capacity construct: acquisition capacity, assimilation capacity, transformation capacity and application capacity. The evaluation model based on entropy weights and interval TOPSIS is established which focuses on measuring absorptive capacity. The practical case study is conducted to illustrate the application of the proposed method for the knowledge absorptive capacity and verify effectiveness and feasibility.