Pairwise Comparison Process Research Articles

Multi Criteria Decision Making Approach for Selecting Effort Estimation Model

Effort Estimation has always been a challenging task for the Project managers. Many researchers have tried to help them by creating different types of models. This has been already proved that none is successful for all types of projects and every type of environment. Analytic Hierarchy Process has been identified as the tool that would help in Multi Criteria Decision Making. Researchers have identified that Analytic Hierarchy Process can be used for the comparison of effort estimation of different models and techniques. But the problem with traditional Analytic Hierarchy Process is its inability to deal with the imprecision and subjectivity in the pairwise comparison process. The motive of this paper is to propose Fuzzy Analytic Hierarchy Process, which can be used to rectify the subjectivity and imprecision of Analytic Hierarchy Process and can be used for selecting the type of Model best suited for estimating the effort for a given problem type or environment. Instead of single crisp value, Fuzzy Analytic Hierarchy Process uses a range of values to incorporate decision maker uncertainty. From this range, decision maker can select the value that reflects his confidence and also he can specify his attitude like optimistic, pessimistic or moderate. In this work, the comparison of Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process is concluded using a case study of selection of effort estimation model.

Measuring the success possibility of implementing ERP by utilizing the Incomplete Linguistic Preference Relations

This paper applies an analytic hierarchical prediction model based on the Multi-Criteria Decision Making with Incomplete Linguistic Preference Relations (InLinPreRa) to help the organizations become aware of the essential factors affecting the Enterprise Resource Planning (ERP), as well as identify the actions necessary before implementing ERP. The subjectivity and vagueness in the prediction procedures are dealt with linguistic variables quantified in an interval [−t, t]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate ERP, inhibit adoption or take remedial actions to increase the success possibility of ERP. Pairwise comparisons are used to determine the priority weights of influential factors, and the possible occurrence ratings of success or failure outcome amongst decision makers. There are not any inconsistency occurred in this procedures because this proposed approach allows every decision expert to choose an explicit criterion or alternative for the without restriction. When there are n criteria in a decision matrix, only n−1 times of pairwise comparisons are taken. This approach not only improves the efficiency of pairwise comparison compared with the traditional AHP, but also avoids the checking the consistency of linguistic preference relation when the decision makers undertake the pairwise comparison processes.

Application of Hybrid VIKOR Model in Selection of Maintenance Strategy

This paper focuses on the use of Fuzzy Analytic Hierarchy Process (FAHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) to select an optimum maintenance strategy for a textile industry. In the proposed methodology, first the weight of each criterion is calculated by using improved AHP with fuzzy set theory to overcome the problems of unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process and then the VIKOR method is applied to compensate the imprecise ranking of the AHP in the selection of maintenance strategy. The real case study is conducted for a textile industry to illustrate the utilization of the proposed model for the maintenance strategy selection problem. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to make sure that the result of the proposed model can be acceptable. A sensitivity analysis is also conducted to show the validity of the proposed model. The paper gives an insight into multi criteria decision-making (MCDM) techniques to select an optimum maintenance strategy for a process industry using a case study.Request access from your librarian to read this article's full text.

Application of fuzzy techniques in a multistage manufacturing system

In previous research by authors, a generalized model has been proposed for a production system and analytic hierarchy process is implemented for the purpose of selection of production control policies in just-in-time environment. In order to handle the inherent uncertainty and imprecision of the pairwise comparison process, the present paper attempts an implementation of fuzzy techniques, i.e., fuzzy–analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution. For the evaluation purpose, a soft experimental design is proposed to measure the parameters for a multiproduct, multistage manufacturing system. Selection of the production policies is made on the basis of various performance measures such as service level, work-in-process, throughput, lost demand, and machine utilization.

Selecting the high - performing departments within universities applying the fuzzy MADM methods

In this study, the process of efficiency measurement is tackled using multi-attribute decision-making (MADM) processes where a sequential algorithm is proposed. The framework of the study is based on two main stages; first, the data envelopment analysis (DEA), separately formulating each pair of units, formulates the department evaluation problem. DEA is a nonparametric multiple criteria method; no production, cost, or profit function is estimated from the data. In the second stage, the pair-wise evaluation matrix generated in the first stage is utilized to fully rank-scale the units via the fuzzy analytical hierarchical process (FAHP). The FAHP method adopted here uses triangular fuzzy numbers (TFN). Inability of AHP to deal with the impression and subjectiveness in the pair-wise comparison process has been improved in Fuzzy AHP. Instead of a crisp value, Fuzzy AHP a range of value to incorporate the decision maker’s uncertainly. Key words: Data envelopment analysis (DEA), fuzzy analytical hierarchy process (FAHP), triangular fuzzy numbers (TFN), multi criteria decision-making (MCDM), multi-attribute decision-making (MADM), fully-rank.

Maintenance Strategy Evaluation Using ANP and Goal Programming

An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance strategy provides valuable cost savings and greater benefits for any hybrid flow systems. For any decision maker, it is convenient to prioritize the criteria of MCDM problems and goals of goal programming problems in fuzzy terms. This paper presents an integrated approach for maintenance policy selection, using fuzzy Analytic Network Process (ANP) within a Goal Programming, based on fuzzy preemptive priority where goal hierarchies are specified in different levels of fuzzy importance. To overcome the criticism of inconsistency, unbalanced scale of judgments and uncertainty in the pair-wise comparison process, criteria weights are determined using modified fuzzy LLSM method.

Joint selection of customs broker agencies and international road transportation firms by a fuzzy analytic network process approach

This paper considers a special case for logistics activities in Turkey: a joint selection of customs broker agency and international road transportation firm. For this purpose a decision-making team has been constituted, including members of logistics and finance departments and an academic. They determined related quantitative and qualitative criteria for the selection process. To cover the vagueness of related qualitative data, a fuzzy analytic network process (FANP) based model was formulated and applied to the decision-making process. The FANP model encompasses and substantially resolves the ambiguity and imprecision of the pairwise comparison process. By using the proposed FANP structure, the joint selection problem could be solved in a much easier way by also considering the inter-dependencies related to criteria.

MBA Students’ preference on: online, formal and hybrid MBA programs

In recent years, there has been a rapid rise in student enrolments in both online and formal MBA programs. This study is based on the results of a case study in which over 30 students enrolled in a top-ranked online and formal MBA program. Thus, the Fuzzy Analytic Hierarchy Process (FAHP) has been used for choosing the program. Due to the inability of AHP to deal with the impression and subjectiveness in the pair-wise comparison process, the FAHP has been used. The result of the research is interesting since neither an online nor a formal education program is preferred; a hybrid one has been developed.

A Hybrid Multiple Criteria Decision Making Technique for Prioritizing Equipments

Prioritization of equipment is an important factor for decision making to optimize maintenance management in Reliability Centered Maintenance (RCM). Many factors must be considered as part of the prioritization of equipment for maintenance activities. Consequently, evaluation procedures involve several objectives and it is often necessary to compromise among conflicting tangible and intangible factors. Multiple Criteria Decision Making (MCDM) is a useful approach to solve these problems. In this study, a hybrid model is developed for prioritizing the equipment in hybrid flow systems. The first stage involves identifying the criteria. The second stage is prioritizing the different criteria using fuzzy Analytical Network Process (ANP), in which the weight of each criterion is calculated using modified fuzzy Logarithmic Least Square Method (LLSM) to overcome the criticism of inconsistency, unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process, then finally ranking of equipment using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

Using the method of pairwise comparison to obtain reliable teacher assessments

Demands for accountability have seen the implementation of large scale testing programs in Australia and internationally. There is, however, a growing body of evidence to show that externally imposed testing programs do not have a sustained impact on student achievement. It has been argued that teacher assessment is more effective in raising student achievement levels. However, it is also often argued that teacher assessments are less reliable than the results of testing programs. This paper presents a study in which teachers judged writing scripts using the process of pairwise comparison to generate a scale. The analysis showed high internal consistency of the teacher judgements. The scale locations from pairwise comparisons were highly correlated with scale estimates for the same students from a large-scale testing program. The results demonstrate it is possible to efficiently obtain highly reliable and valid teacher judgements using the process of pairwise comparison. Reliability indices are also provided for a series of small-scale assessments that used the same methodology in a range of other domains. The results support the findings of the main study. The article discusses the benefits of using the method to supplement and validate results from large-scale testing programs.

Modeling subjective evaluation for fuzzy group multicriteria decision making

This paper presents a new fuzzy multicriteria decision making (MCDM) approach for evaluating decision alternatives involving subjective judgements made by a group of decision makers. A pairwise comparison process is used to help individual decision makers make comparative judgements, and a linguistic rating method is used for making absolute judgements. A hierarchical weighting method is developed to assess the weights of a large number of evaluation criteria by pairwise comparisons. To reflect the inherent imprecision of subjective judgements, individual assessments are aggregated as a group assessment using triangular fuzzy numbers. To obtain a cardinal preference value for each decision alternative, a new fuzzy MCDM algorithm is developed by extending the concept of the degree of optimality to incorporate criteria weights in the distance measurement. An empirical study of aircraft selection is presented to illustrate the effectiveness of the approach.

Mutation-selection equilibrium in games with multiple strategies

In evolutionary games the fitness of individuals is not constant but depends on the relative abundance of the various strategies in the population. Here we study general games among n strategies in populations of large but finite size. We explore stochastic evolutionary dynamics under weak selection, but for any mutation rate. We analyze the frequency dependent Moran process in well-mixed populations, but almost identical results are found for the Wright–Fisher and Pairwise Comparison processes. Surprisingly simple conditions specify whether a strategy is more abundant on average than 1 / n , or than another strategy, in the mutation-selection equilibrium. We find one condition that holds for low mutation rate and another condition that holds for high mutation rate. A linear combination of these two conditions holds for any mutation rate. Our results allow a complete characterization of n × n games in the limit of weak selection.

Balanced score for the balanced scorecard: a benchmarking tool

PurposeThe purpose of this paper is to create a model called “Balanced score for the balanced score card” and to provide an objective benchmarking indicator for evaluating the achievement of the strategic goals of the company.Design/methodology/approachThe paper uses the concepts of “Balanced scorecard” proposed by Robert. S. Kaplan and David P. Norton. This paper also adopts the model given by Brown P.A. and Gibson D.F. and the extension to the model provided by P.V. Raghavan and M. Punniyamoorthy. Preference theory is used to calculate the relative weightage for each factor, using the process of pair wise comparison. The balanced score for balanced scorecard provides a single value by taking into account all the essential objective and subjective factors – be it financial or non‐financial. It also provides a suitable weightages for those parameters. The target performance and the actual performance are compared and the analysis is made.FindingsInformation from a leading organization was obtained and the balanced score for a balance scorecard was calculated for that organization. The variations were analyzed through this model. The depth and objectivity in the analysis is highlighted.Research limitations/implicationsThis provides a single bench marking measure to evaluate how far the firm had been successful in achieving the strategies. The paper has adopted the preference theory which limits the weightage to be accorded to the factors concerned. However, further refinement can be provided by the usage of analytic hierarchy process for arriving suitable weightages.Practical implicationsThe organization can calculate the balanced score by themselves, by assigning appropriate importance to the activities – as they deem fit. It is a tailor made benchmarking information system created by the firm for itself.Originality/valueThis is of value to the top management to identify the important activities and setting suitable target measures to be achieved in those activities. The variations are arrived by comparing the targeted performance with the actual. This will help the firm to take suitable actions under those parameters where there are significant deviations.

Drift reversal in asymmetric coevolutionary conflicts: influence of microscopic processes and population size

The coevolutionary dynamics in finite populations currently is investigated in a wide range of disciplines, as chemical catalysis, biological evolution, social and economic systems. The dynamics of those systems can be formulated within the unifying framework of evolutionary game theory. However it is not a priori clear which mathematical description is appropriate when populations are not infinitely large. Whereas the replicator equation approach describes the infinite population size limit by deterministic differential equations, in finite populations the dynamics is inherently stochastic which can lead to new effects. Recently, an explicit mean-field description in the form of a Fokker-Planck equation was derived for frequency-dependent selection in finite populations based on microscopic processes. In asymmetric conflicts between two populations with a cyclic dominance, a finite-size dependent drift reversal was demonstrated, depending on the underlying microscopic process of the evolutionary update. Cyclic dynamics appears widely in biological coevolution, be it within a homogeneous population, or be it between disjunct populations as female and male. Here explicit analytic address is given and the average drift is calculated for the frequency-dependent Moran process and for different pairwise comparison processes. It is explicitely shown that the drift reversal cannot occur if the process relies on payoff differences between pairs of individuals. Further, also a linear comparison with the average payoff does not lead to a drift towards the internal fixed point. Hence the nonlinear comparison function of the frequency-dependent Moran process, together with its usage of nonlocal information via the average payoff, is the essential part of the mechanism.

A survey and optimization-based evaluation of development strategies for the air cargo industry

This paper presents a survey and optimization-based approach to evaluating alternative strategies proposed for the development of a national's air cargo industry. An empirical study of Taiwan's air cargo industry is conducted to illustrate how the approach integrates experts’ opinions from three stakeholder groups (the government, the academic, and the carrier) about the relative importance and achievability of 18 alternative strategies. To help experts weight alternative strategies subjectively, a new hierarchical pairwise comparison process is used, with the ratio scale represented by triangular fuzzy numbers. In judging the achievability level of alternative strategies, linguistic variables represented by triangular fuzzy numbers are used. To ensure the acceptability of the evaluation result, a carrier oriented optimal weighting approach is developed for maximizing the overall preference value of the carriers, subject to the weight ranges specified by the government and academic experts. The overall preference and ranking of the alternative strategies are made by aggregating the optimal weights with their achievability level. The approach has general application in evaluating policy alternatives by taking account of subjective judgments of different stakeholder groups.

Prioritizing management issues of moving dangerous goods by air transport

This paper presents an expert survey-based approach for prioritizing management issues of dangerous goods transportation faced by air-transport-related sectors in Taiwan. A two-stage survey process is used to ask the experts to first identify and then evaluate the management issues. To develop effective-management priorities, these issues are evaluated in terms of their importance, urgency, achievability, and effectiveness, based on experts’ comparative and absolute judgments. A pairwise comparison process is used to help the experts make comparative judgments, while a linguistic rating method is used for absolute judgments. To reflect the inherent imprecision involved in the survey process, experts’ assessments are represented by triangular fuzzy numbers. To obtain an overall priority value, a fuzzy multiattribute decision-making method is used.

Expediting and standardizing stone artifact refitting using a computerized suitability model

Stone artifact refitting is a valuable aspect of archaeological research and can inform on a variety of issues, such as prehistoric technology, site taphonomy, and assemblage patterning and function. It offers a means of teasing apart sites with complicated occupational histories and is particularly useful in interpreting surface lithic scatters, the dominant site type across much of the globe. Unfortunately, refitting is also labor intensive and time-consuming, especially for the inexperienced refitting analyst, making it logistically challenging in the case of many research projects. A possible solution is proposed by which the process of refitting might be partially automated. A multivariate suitability model was created in a Geographic Information Systems (GIS) environment. The refitting suitability model first eliminates low probability refits, and then ranks the remaining artifacts according to a score that reflects their likelihood of refitting to a target artifact. Scores are assigned to assemblage items based on a series of criteria, including raw material, cortex, size, and spatial proximity. In this pilot study, known refits from 5GN149, a surface lithic scatter in Colorado, USA, were used to test the accuracy of the model. The refitting suitability model correctly placed the known refit at the top of the list of potential refits (i.e., assigned a rank to the known refit ranging from 1 to 10) approximately 32% of the time. This is more refit identifications than would be expected through a process of pair-wise comparisons. Preliminary results suggest that the model has the potential to standardize and expedite the process of refitting.

Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process

Background:Biological Mass Spectrometry is used to analyse peptides and proteins. A mass spectrum generates a list of measured mass to charge ratios and intensities of ionised peptides, which is called a peak-list. In order to classify the underlying amino acid sequence, the acquired spectra are usually compared with synthetic ones. Development of suitable methods of direct peak-list comparison may be advantageous for many applications.Results:The pairwise peak-list comparison is a multistage process composed of matching of peaks embedded in two peak-lists, normalisation, scaling of peak intensities and dissimilarity measures. In our analysis, we focused on binary and intensity based measures. We have modified the measures in order to comprise the mass spectrometry specific properties of mass measurement accuracy and non-matching peaks. We compared the labelling of peak-list pairs, obtained using different factors of the pairwise peak-list comparison, as being the same or different to those determined by sequence database searches. In order to elucidate how these factors influence the peak-list comparison we adopted an analysis of variance type method with the partial area under the ROC curve as a dependent variable.Conclusion:The analysis of variance provides insight into the relevance of various factors influencing the outcome of the pairwise peak-list comparison. For large MS/MS and PMF data sets the outcome of ANOVA analysis was consistent, providing a strong indication that the results presented here might be valid for many various types of peptide mass measurements.

Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network

The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data.

Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics

Product semantics, the “study of the symbolic qualities of man-made forms in the context of their use, and application of this knowledge to industrial design” is an important challenge in product design. Because of subjectivity, this particular dimension of the user's need is difficult to express, to quantify and to assess. This paper presents a general approach to assess product semantics in a sound way. It is based on usability tests, and involves several classical methods in marketing and decision-making theory, as multidimensional scaling, semantic differential method, factor analysis, pairwise comparison and analytical hierarchy process. As a result, our integrated approach provides designers with a tool which helps understand and specify the semantic part of the need; it rates and ranks the new product prototypes according to their closeness to the specified “ideal product”, and it underlines the particular semantic dimensions that should be improved. To illustrate our approach, we have performed usability tests and applied our methodology to the design of table glasses. For the sake of clarity, each stage of the methodology is presented in detail on this particular example. Relevance to industry The integrated framework proposed in this paper can be readily deployed in companies and used at different stages of the design of products. Firstly, our methodology provides a frame for describing how a given products family is perceived by users, and for storing and up-dating these data. Secondly, the data can be used to specify target requirements for a new product by qualitative comparisons to existing products. Finally, emerging product concepts may be directly assessed with regards to the requirements in a simple qualitative and comparative way.