A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

Economic analyses for the evaluation of is projects

Information system projects usually have numerous uncertainties and several conditions of risk that make their economic evaluation a challenging task. Each year, several information system projects are cancelled before completion as a result of budget overruns at a cost of several billions of dollars to industry. Although engineering economic analysis offers tools and techniques for evaluating risky projects, the tools are not enough to place information system projects on a safe budget/selection track. There is a need for an integrative economic analysis model that will account for the uncertainties in estimating project costs benefits and useful lives of uncertain and risky projects. The fuzzy set theory has the capability of representing vague data and allows mathematical operators and programming to be applied to the fuzzy domain. The theory is primarily concerned with quantifying the vagueness in human thoughts and perceptions. In this article, the economic evaluation of information system projects using fuzzy present value and fuzzy B/C ratio is analyzed. A numerical illustration is included to demonstrate the effectiveness of the proposed methods

Fuzzy net present value for engineering analysis

Cash flow analysis is one of the most popular methods for investigating the outcome of an economical project. The costs and benefits of a construction project are often involved with uncertainty and it is not possible to find a precise value for a particular project. In this paper, we present a simple method to calculate the net present value of a cash flow when both costs and benefits are given as triangular numbers. The proposed model of this paper uses Delphi method to figure out the fair values of all costs and revenues and then using fizzy programming techniques, it calculates the fuzzy net present value. The implementation of the proposed model is demonstrated using a simple example

Portfolio optimization using a hybrid of fuzzy ANP, VIKOR and TOPSIS

One of the primary questions in asset management is to find good combinations of different assets and this has been an interesting area of research for over half a century. The proposed model of this paper uses decision makers' feedbacks based on multiple criteria decision making technique to find an appropriate portfolio. We first select some important financial criteria and then using decision makers' opinions and by implementation of some fuzzy network analysis we find appropriate weights of the asset. The proposed model uses two multiple criteria techniques namely TOPSIS and VIKOR and the model is examined for some real-world data from Tehran Stock Exchange. The results of the implementation of the proposed model have been examined against Markowitz traditional model. The preliminary results indicate that the proposed model of this paper performs reasonably well compared with alternative method

Capturing Risk in Capital Budgeting

NPS NRP Technical ReportThis proposed research has the goal of proposing novel, reusable, extensible, adaptable, and comprehensive advanced analytical process and Integrated Risk Management to help the (DOD) with risk-based capital budgeting, Monte Carlo risk-simulation, predictive analytics, and stochastic optimization of acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The research covers topics of traditional capital budgeting methodologies used in industry, including the market, cost, and income approaches, and explains how some of these traditional methods can be applied in the DOD by using DOD-centric non-economic, logistic, readiness, capabilities, and requirements variables. Stochastic portfolio optimization with dynamic simulations and investment efficient frontiers will be run for the purposes of selecting the best combination of programs and capabilities is also addressed, as are other alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. The results include actionable intelligence developed from an analytically robust case study that senior leadership at the DOD may utilize to make optimal decisions. The main deliverables will be a detailed written research report and presentation brief on the approach of capturing risk and uncertainty in capital budgeting analysis. The report will detail the proposed methodology and applications, as well as a summary case study and examples of how the methodology can be applied.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

A fuzzy levelised energy cost method for renewable energy technology assessment

Renewable energy project development is highly complex and success is by no means guaranteed. Decisions are often made with approximate or uncertain information yet the current methods employed by decision-makers do not necessarily accommodate this. Levelised energy costs (LEC) are one such commonly applied measure utilised within the energy industry to assess the viability of potential projects and inform policy. The research proposes a method for achieving this by enhancing the traditional discounting LEC measure with fuzzy set theory. Furthermore, the research develops the fuzzy LEC (F-LEC) methodology to incorporate the cost of financing a project from debt and equity sources. Applied to an example bioenergy project, the research demonstrates the benefit of incorporating fuzziness for project viability, optimal capital structure and key variable sensitivity analysis decision-making. The proposed method contributes by incorporating uncertain and approximate information to the widely utilised LEC measure and by being applicable to a wide range of energy project viability decisions

Giga-Investments: Modelling the Valuation of Very Large Industrial Real Investments

In this doctoral dissertation characteristics of very large industrial real investments (VLIRI) are investigated and a special group of VLIRI is defined as giga-investments. The investment decision-making regarding to giga-investments is discussed from the points of view of discounted cash-flow based methods and real option valuation. Based on the bacground of establishing giga-investments, state-of-the-art in capital budgeting (including real options) and by applying fuzzy numbers a novel method for the evaluation and profitability analysis of giga-investments is presented. Application of the method is illustrated and issues regarding investment decision-making of large industrial real investments are discussed.Real Options; Fuzzy Real Option Valuation; Giga-Investments; Very Large Industrial Real Investments; Dissertation

Multi criteria operating system selection using fuzzy replacement analysis and AHP

Bu çalışma Karar Alıcılar (KA) için İşlem Sistemi (İS) seçim sistemi kurmayı hedeflemektedir. Karar Alıcılar teknoloji seçiminde hem ekonomik hem de ekonomik olmayan unsurları göz önüne almak zorunda olduklarından, geliştirilen sistemde her iki unsura da yer verilmiştir. Karar alma sürecinin ekonomik yanı, Bulanık Yenileme Analizi kullanılarak geliştirilmiştir. Ekonomik olamayan unsurlar ve finansal veriler ise Bulanık Analitik Hiyerarşi Süreci (AHS) yaklaşımı kullanılarak biraraya getirilmiştir. Çalışma içerisinde aynı zamanda sayısal bir örneğe de yer verilmiştir. AHS yaklaşımının finansal yönü geliştirilen Bulanık Yenileme Analizi altyapısı tarafından desteklenmiştir. Bulanık AHS yönteminin Mühendislik Ekonomisi’nin ana konularından olan Yenileme Analizleri’nde kullanılması araştırmacılara yatırım alternatiflerinin değerlendirilmesinde etkin yollar sağlamaktadır.Anahtar Kelimeler: Bulanık kümeler, yenileme analizleri, analitik hiyerarşi süreci, teknoloji seçimi.This study aims at creating an Operating System (OS) selection framework for decision makers (DMs). Since DMs have to consider both economic and non-economic aspect of technology selection, both factors have been considered in the developed framework. The economic part of the decision process has been developed by Fuzzy Replacement Analysis. Non-economic factors ve financial figures have been combined using Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach. A real numerical application has also been demonstrated. This study developed a fuzzy AHP framework to select best OS alternative. While fuzzy AHP requires cumbersome computations, it is a more systematic method than the others are, and it is more capable of capturing a human?s appraisal of ambiguity when complex multi-attribute decision-making problems are considered. This is true because pairwise comparisons provide a flexible and realistic way to accommodate real-life data. The financial side of the framework is based on fuzzy replacement analysis. The results of fuzzy replacement analysis are included into fuzzy AHP analysis. Using Fuzzy AHP concept in Replacement Analysis investment decisions in fuzzy environment results a very effective way to evaluate alternatives. Using the very same developed framework, a subjective comparison, such as the comparison of diverse operating systems, has been conducted and demonstrated to readers.Keywords: Fuzzy sets, replacement analysis, AHP, technology selection