Search results for: uncertainty decision analysis

Authors: C. Ardil

Abstract:

Intuitionistic fuzzy sets (IFS), Pythagorean fuzzy sets (PyFS), Picture fuzzy sets (PFS), q-rung orthopair fuzzy sets (q-ROF), Spherical fuzzy sets (SFS), T-spherical FS, and Neutrosophic sets (NS) are reviewed as multidimensional extensions of fuzzy sets in order to more explicitly and informatively describe the opinions of decision-making experts under uncertainty. To handle operations with standard fuzzy sets (SFS), the necessary operators; weighted arithmetic mean (WAM), weighted geometric mean (WGM), and Minkowski distance function are defined. The algorithm of the proposed proximity measure method (PMM) is provided with a multiple criteria group decision making method (MCDM) for use in a standard fuzzy set environment. To demonstrate the feasibility of the proposed method, the problem of selecting the best drone for an Air Force procurement request is used. The proximity measure method (PMM) based multidimensional standard fuzzy sets (SFS) is introduced to demonstrate its use with an issue involving unmanned combat aircraft selection.

Keywords: standard fuzzy sets (SFS), unmanned combat aircraft selection, multiple criteria decision making (MCDM), proximity measure method (PMM).

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Authors: Peter Boyes, Sarah Sharples, Paul Tennent, Gary Priestnall, Jeremy Morley

Abstract:

Significant long-term investment projects can involve complex decisions. These are often described as capital projects and the factors that contribute to their complexity include budgets, motivating reasons for investment, stakeholder involvement, interdependent projects, and the delivery phases required. The complexity of these projects often requires management groups to be established involving stakeholder representatives, these teams are inherently multidisciplinary. This study uses two university campus capital projects as case studies for this type of management group. Due to the interaction of projects with wider campus infrastructure and users, decisions are made at varying spatial granularity throughout the project lifespan. This spatial-related context brings complexity to the group decisions. Sensemaking is the process used to achieve group situational awareness of a complex situation, enabling the team to arrive at a consensus and make a decision. The purpose of this study is to understand the role of people and data in complex spatial related long-term decision and sensemaking processes. The paper aims to identify and present issues experienced in practical settings of these types of decision. A series of exploratory semi-structured interviews with members of the two projects elicit an understanding of their operation. From two stages of thematic analysis, inductive and deductive, emergent themes are identified around the group structure, the data usage, and the decision making within these groups. When data were made available to the group, there were commonly issues with perception of veracity and validity of the data presented; this impacted the ability of the group to reach consensus and therefore for decision to be made. Similarly, there were different responses to forecasted or modelled data, shaped by the experience and occupation of the individuals within the multidisciplinary management group. This paper provides an understanding of further support required for team sensemaking and decision making in complex capital projects. The paper also discusses the barriers found to effective decision making in this setting and suggests opportunities to develop decision support systems in this team strategic decision-making process. Recommendations are made for further research into the sensemaking and decision-making process of this complex spatial-related setting.

Keywords: decision making, decisions under uncertainty, real decisions, sensemaking, spatial, team decision making

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Authors: Seung hee Kang, Jee-Hong Kim, Ji Seong Jang,

Abstract:

The purpose of this study was to investigate relationships between satisfaction with major and career decision efficacy and career attitude maturity of engineering college students by performing correlation analysis. Gender differences in between satisfaction with major and career decision efficacy and career attitude maturity were also examined by T-test. The results T-test revealed gender differences in only career decision efficacy. Male Students scored significantly higher than did female students on career decision efficacy and satisfaction with major. The results of correlation analysis showed a) satisfaction with major were significantly associated with career decision efficacy, b) satisfaction with major were significantly associated with career attitude maturity, and c) career decision efficacy were significantly associated with career attitude maturity. As a result,we found the importance of satisfaction in engineering college students- major studies when deciding their career.

Keywords: Satisfaction with major, career decision efficacy, career attitude maturity, engineering college student.

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Authors: Christiono Utomo, Arazi Idrus

Abstract:

Value-based group decision is very complicated since many parties involved. There are different concern caused by differing preferences, experiences, and background. Therefore, a support system is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. The support system is based on combination between value-based analysis, multi criteria group decision making based on satisfying options, and negotiation process based on coalition formation. This paper presents the group decision and negotiation on the selection of suitable material for a support bridge structure involving three decision makers, who are an estate manager, a project manager, and an engineer. There are three alternative solutions for the material of the support bridge structure, which are (a1) steel structure, (a2) reinforced concrete structure and (a3) wooden structure.

Keywords: Value-based, group decision, negotiation support, construction.

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Authors: Abdallah A. Hlayel

Abstract:

Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that effect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decisionmaking.

Keywords: Best candidates' method, decision making, decision support system, operations research.

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Authors: K. M. Alsager, N. O. Alshehri

Abstract:

In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example.

Keywords: Single valued neutrosophic hesitant set, single valued neutrosophic hesitant relation, single valued neutrosophic hesitant fuzzy rough set, decision making method.

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Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov

Abstract:

One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.

Keywords: Fuzzy logic, fuzzy sets, performance measurement, project analysis.

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Authors: Gökhan Silahtaroğlu

Abstract:

Decision tree algorithms have very important place at classification model of data mining. In literature, algorithms use entropy concept or gini index to form the tree. The shape of the classes and their closeness to each other some of the factors that affect the performance of the algorithm. In this paper we introduce a new decision tree algorithm which employs data (attribute) folding method and variation of the class variables over the branches to be created. A comparative performance analysis has been held between the proposed algorithm and C4.5.

Keywords: Classification, decision tree, split, pruning, entropy, gini.

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Authors: Babak Tashakori Bafghi, Laleh Tashakori, Reza Allahyari Soeini, Mohammad Mokhtari

Abstract:

Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.

Keywords: Knapsack, linear programming, supplier select, supply chain management.

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Authors: H. Rafiei, M. Rabbani

Abstract:

This paper proposes a new decision making structure to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder, and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company. The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.

Keywords: Hybrid make-to-stock/make-to-order, Multi-attribute decision making, Order partitioning, Order penetration point.

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Authors: Yi Xu, Zexiang Li

Abstract:

In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.

Keywords: eigenvalue-optimal optimization, freeform surface inspection, sampling size and location, sampled points.

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Authors: Barbora Chmelíková

Abstract:

Making sound financial decisions is an essential skill which can have an impact on life of each consumer of financial products. The aim of this paper is to examine decision-making concerning financial matters and personal finance. The selected target group was university students majoring in finance related fields. The study was conducted in the Czech Republic at Masaryk University in 2015. In order to analyze financial decision-making questions related to basic finance decisions were developed to address the research objective. The results of the study suggest gaps in detecting best solutions to given financial decision-making questions among finance students. The analysis results indicate relation between financial decision-making and own experience with holding and using concrete financial products.

Keywords: Financial decision-making, financial literacy, personal finance, university students.

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Authors: Pulak Swain, A. K. Ojha

Abstract:

Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: Portfolio optimization, multi-objective optimization, E-constraint method, box uncertainty, robust optimization.

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Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara

Abstract:

In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.

Keywords: Stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.

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Authors: R. Monib, C. I. Goodier, A. Gibb

Abstract:

This paper aims to investigate decision support strategies in the EC sector to determine the most appropriate degree of modularization. This is achieved through three oil and gas (O&G) and two power plant case studies via semi-structured interviews (n = 59 and n = 27, respectively), analysis of project documents, and case study-specific semi-structured validation interviews (n = 12 and n = 8). Terminology to distinguish degrees of modularization is proposed, along with a decision-making support checklist and a diagrammatic decision-making support figure. Results indicate that the EC sub-sectors were substantially more satisfied with the application of component, structural, or traditional modularization compared with system modularization for some types of modules. Key drivers for decisions on the degree of modularization vary across module types. This paper can help the EC sector determine the most suitable degree of modularization via a decision-making support strategy.

Keywords: Modularization, engineering construction, case study, decision support.

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Authors: Reza Ebrahimpour, Samaneh Hamedi

Abstract:

Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. The extracted feature vector is fed to multiple classifier fusion. A set of experiments were conducted to compare decision templates (DTs) with some combination rules. Results from decision templates conclude 97.99% and 97.28% for Farsi and English handwritten digits.

Keywords: Decision templates, multi-layer perceptron, characteristics Loci, principle component analysis (PCA).

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Authors: Manisha Rathi, Thierry Chaussalet

Abstract:

Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.

Keywords: Admission, Fuzzy, Regression, Uncertainty

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Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

Abstract:

The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: Artificial neural networks, cellular automata, decision support system, pattern recognition.

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Authors: Radomir Perzina, Jaroslav Ramik

Abstract:

The Analytic Hierarchy Process is frequently used approach for solving decision making problems. There exists wide range of software programs utilizing that approach. Their main disadvantage is that they are relatively expensive and missing intermediate calculations. This work introduces a Microsoft Excel add-in called DAME – Decision Analysis Module for Excel. Comparing to other computer programs DAME is free, can work with scenarios or multiple decision makers and displays intermediate calculations. Users can structure their decision models into three levels – scenarios/users, criteria and variants. Items on all levels can be evaluated either by weights or pair-wise comparisons. There are provided three different methods for the evaluation of the weights of criteria, the variants as well as the scenarios – Saaty’s Method, Geometric Mean Method and Fuller’s Triangle Method. Multiplicative and additive syntheses are supported. The proposed software package is demonstrated on couple of illustrating examples of real life decision problems.

Keywords: Analytic hierarchy process, multi-criteria decision making, pair-wise comparisons, Microsoft Excel, Scenarios.

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Authors: Gülcin Büyüközkan, Mehmet Sakir Ersoy

Abstract:

The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourcing suppliers. An axiomatic design based fuzzy group decision making is adopted to evaluate supplier alternatives. Finally, a case study is given to demonstrate the potential of the methodology. KeywordsIT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic.

Keywords: IT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic

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Authors: Karin Hansson, Göran Cars, Mats Danielson, Love Ekenberg, Aron Larsson

Abstract:

Within the realm of e-government, the development has moved towards testing new means for democratic decisionmaking, like e-panels, electronic discussion forums, and polls. Although such new developments seem promising, they are not problem-free, and the outcomes are seldom used in the subsequent formal political procedures. Nevertheless, process models offer promising potential when it comes to structuring and supporting transparency of decision processes in order to facilitate the integration of the public into decision-making procedures in a reasonable and manageable way. Based on real-life cases of urban planning processes in Sweden, we present an outline for an integrated framework for public decision making to: a) provide tools for citizens to organize discussion and create opinions; b) enable governments, authorities, and institutions to better analyse these opinions; and c) enable governments to account for this information in planning and societal decision making by employing a process model for structured public decision making.

Keywords: Negotiation games, Agenda setting, Multi-criteria decision analysis, Elicitation method.

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Authors: Niina M. Nissinen

Abstract:

This paper introduces an approach to construct a set of criteria for evaluating alternative options. Content analysis was used to collet criterion elements. Then the elements were classified and organized yielding to hierarchic structure. The reliability of the constructed criteria was evaluated in an experiment. Finally the criteria were used to evaluate alternative options indecision-making.

Keywords: Conceptual analysis, Content Analysis, Criteria, Decision-Making, Evaluation of Candidates

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

Abstract:

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: C. Ardil

Abstract:

This paper introduces a new method for multiplecriteria decision making (MCDM) that avoids order reversal and ensures consistency in decision-making. The proposed method involves range targeting of benefit and cost criteria vectors for range normalization of the initial decision matrix. The Reference Linear Combination (RLC) is used to avoid the rank reversal problem. The preference order generated from the target score matrix does not require relative comparisons between alternatives but relies on a chosen reference solution point after transforming the original decision matrix into an MCDM problem by specifying the minimum and maximum bounds of each criterion. The efficiency and applicability of the proposed RLC method were demonstrated in the selection of commercial passenger aircraft. 

Keywords: Aircraft selection, reference linear combination (RLC), multiple criteria decision-making, MCDM

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Authors: Wiem Daoud Ben Amor, Luis Martínez López, Jr., Hela Moalla Frikha

Abstract:

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain context where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ELH-ARAS). Within the ELH-ARAS approach, the decision maker (DMs) can diagnose the results (the ranking of the alternatives) in a decomposed style i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e., the collective final results of all experts are able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ELH-ARAS technique makes it easier for decision-makers to understand the results. Finally, an MCGDM case study is given to illustrate the proposed approach.

Keywords: Additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts.

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Authors: C. Ardil

Abstract:

Aircraft selection decisions can be challenging due to their multidimensional and interdisciplinary nature. They involve multiple stakeholders with conflicting objectives and numerous alternative options with uncertain outcomes. This study focuses on the analysis of aerial firefighting aircraft that can be chosen for the Air Fire Service to extinguish forest fires. To make such a selection, the characteristics of the fire zones must be considered, and the capability to manage the logistics involved in such operations, as well as the purchase and maintenance of the aircraft, must be determined. The selection of firefighting aircraft is particularly complex because they have longer fleet lives and require more demanding operation and maintenance than scheduled passenger air service. This paper aims to use the fuzzy proximity measure method to select the most appropriate aerial firefighting aircraft based on decision criteria using multiple attribute decision making analysis. Following fuzzy decision analysis, the most suitable aerial firefighting aircraft is ranked and determined for the Air Fire Service.

Keywords: Aerial firefighting aircraft selection, multiple criteria decision making, fuzzy sets, standard fuzzy sets, determinate fuzzy sets, indeterminate fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, MCDM, PMM, PMM-F

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Authors: B. Mikulskienė

Abstract:

Public administration institutions in cooperation with politicians are not the sole policy decision makers in full meaning any longer. Meanwhile, a special role, namely steering the decision making process, could be delegated to them. Despite the wide scientific discussion on different aspects what has direct impact on policy creation, there is a lack of holistic practical managerial advice, which could integrate infrastructure of policy decision making with intellectual capital and with interconnection of partnership. The proposed harmonized decision making model of process, people and partnership entitled by acronym HM-3P is analyzed as a framework for implementation of public administration steering role seeking the coherent social involvement in policy decision making.

Keywords: participatory decision making, partnership, stakeholders.

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

Abstract:

One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: Wind power, Uncertainty, Stochastic process, Monte Carlo simulation.

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Authors: C. Ardil

Abstract:

In this research, a multidimensional  compromise optimization method is proposed for multidimensional decision making analysis in the development ranking of the Gulf Cooperation Council Countries and Turkey. The proposed approach presents ranking solutions resulting from different multicriteria decision analyses, which yield different ranking orders for the same ranking problem, consisting of a set of alternatives in terms of numerous competing criteria when they are applied with the same numerical data. The multiobjective optimization decision making problem is considered in three sequential steps. In the first step, five different criteria related to the development ranking are gathered from the research field. In the second step, identified evaluation criteria are, objectively, weighted using standard deviation procedure. In the third step, a country selection problem is illustrated with a numerical example as an application of the proposed multidimensional  compromise optimization model. Finally, multidimensional  compromise optimization approach is applied to rank the Gulf Cooperation Council Countries and Turkey. 

Keywords: Standard deviation, performance evaluation, multicriteria decision making, multidimensional compromise optimization, vector normalization, multicriteria decision making, multicriteria analysis, multidimensional decision analysis.

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Authors: C. Ardil

Abstract:

This paper presents an original application of multiple criteria decision making analysis theory to the evaluation of aircraft selection problem. The selection of an optimal, efficient and reliable fleet, network and operations planning policy is one of the most important factors in aircraft selection problem. Given that decision making in aircraft selection involves the consideration of a number of opposite criteria and possible solutions, such a selection can be considered as a multiple criteria decision making analysis problem. This study presents a new integrated approach to decision making by considering the multiple criteria utility theory and the maximal regret minimization theory methods as well as aircraft technical, economical, and environmental aspects. Multiple criteria decision making analysis method uses different normalization techniques to allow criteria to be aggregated with qualitative and quantitative data of the decision problem. Therefore, selecting a suitable normalization technique for the model is also a challenge to provide data aggregation for the aircraft selection problem. To compare the impact of different normalization techniques on the decision problem, the vector, linear (sum), linear (max), and linear (max-min) data normalization techniques were identified to evaluate aircraft selection problem. As a logical implication of the proposed approach, it enhances the decision making process through enabling the decision maker to: (i) use higher level knowledge regarding the selection of criteria weights and the proposed technique, (ii) estimate the ranking of an alternative, under different data normalization techniques and integrated criteria weights after a posteriori analysis of the final rankings of alternatives. A set of commercial passenger aircraft were considered in order to illustrate the proposed approach. The obtained results of the proposed approach were compared using Spearman's rho tests. An analysis of the final rank stability with respect to the changes in criteria weights was also performed so as to assess the sensitivity of the alternative rankings obtained by the application of different data normalization techniques and the proposed approach.

Keywords: Normalization Techniques, Aircraft Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA

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