Qualitative Decision Research Articles

Research on Forces Optimization of Communications Countermeasure Reconnaissance Based on Linear Programming

At present, the force assignment of communications countermeasure reconnaissance was decided by qualitative analysis method. In view of the limitation of the qualitative decision, minimized force of communications countermeasure reconnaissance was taken as the objective function, minimized watchers of every time bucket and maximized the duration time on every watcher were taken as the constraint condition, the mathematical model of forces optimization of communications countermeasure reconnaissance was built with linear programming, which was non-standard linear programming. And the mathematical model was solved by simplex method. The result of example showed that the forces optimization of communications countermeasure reconnaissance was valid, and could provide the scientific method for optimization the forces of communications countermeasure reconnaissance.

Lexicographic refinements in possibilistic decision trees and finite-horizon Markov decision processes

Possibilistic decision theory has been proposed twenty years ago and has had several extensions since then. Even though appealing for its ability to handle qualitative decision problems, possibilistic decision theory suffers from an important drawback. Qualitative possibilistic utility criteria compare acts through min and max operators, which leads to a drowning effect. To overcome this lack of decision power of the theory, several refinements have been proposed. Lexicographic refinements are particularly appealing since they allow to benefit from the Expected Utility background, while remaining qualitative. This article aims at extending lexicographic refinements to sequential decision problems i.e., to possibilistic decision trees and possibilistic Markov decision processes, when the horizon is finite. We present two criteria that refine qualitative possibilistic utilities and provide dynamic programming algorithms for calculating lexicographically optimal policies.

Modeling complex linguistic expressions in qualitative decision making: An overview

The increasing complexity of real-world problems drives the experts to consider complex linguistic expressions instead of single linguistic terms to represent their linguistic opinions under uncertainties. Based on some classical linguistic representational models, a number of techniques of modeling complex linguistic expressions have been proposed. The main purpose of this paper is to present a systematical overview on these techniques, especially their focused linguistic expressions and the associated computational essentials. According to the features of the underlying linguistic expressions, the existing techniques are classified into two categories: the models of natural linguistic expressions, such as uncertain linguistic terms and hesitant fuzzy linguistic term sets, which focus on frequently used expressions in natural languages, and the models of artificial linguistic expressions, such as discrete fuzzy numbers and probabilistic linguistic term sets, which consider special types of expressions artificially constructed by linguistic terms and additional information. After the presentation of comparative analyses on the existing techniques, we figure out some current challenges and provide some possible directions for further developments.

Prediction of software quality using neuro-fuzzy model

In the era of digital systems, management of software project is the biggest challenge. So, early prediction of software quality plays a vital role in the software industry. It helps the management to take the qualitative decisions. In this paper the prediction model proposed by us is a hybrid one with the combination of neural network and fuzzy logic, which discards their individual limitations. This model provides some features which are able to deal with various objectives at the time of software development process. Using this model the prediction of software quality can be measured that also helps in checking the errors and avoiding the expense of redoing.

Prediction of software quality using neuro-fuzzy model

In the era of digital systems, management of software project is the biggest challenge. So, early prediction of software quality plays a vital role in the software industry. It helps the management to take the qualitative decisions. In this paper the prediction model proposed by us is a hybrid one with the combination of neural network and fuzzy logic, which discards their individual limitations. This model provides some features which are able to deal with various objectives at the time of software development process. Using this model the prediction of software quality can be measured that also helps in checking the errors and avoiding the expense of redoing.

Linguistic terms with weakened hedges: A model for qualitative decision making under uncertainty

When expressing the experts’ opinions in qualitative decision making (QDM), linguistic hedges can be considered to modify the force expressed by a predefined linguistic term. If an expert is not sure to select one term, weakened hedges would be a natural way to express the uncertainty. This is usually implemented by using a hedge to modify the most possible term, like the expression “more or less good”. To model the uncertainty implied by hedges in QDM, this paper presents a novel linguistic representational and computational model in which the linguistic expressions take the form of a weakened hedge and a linguistic term, which is named as linguistic term with weakened hedge (LTWH). The syntax of LTWHs is defined by a set of hedges and a set of linguistic terms. The semantics of a LTWH is determined, objectively, based on the semantics of the term and a similarity measure of the reference domain. Accordingly, the negation, order relations and some basic operations of LTWHs are defined. To illustrate the effectiveness of LTWHs in granular computing, the connection to some multi-granularity linguistic models is exploited and a process for unifying multi-granularity linguistic information is developed. The major contritions of this paper are: (1) The proposed model enables a new manner to express and operate uncertain linguistic information in QDM; (2) it possesses clear syntax and semantics and the computational results are very interpretable; and (3) the proposed solution of multi-granularity linguistic unification maintains the semantics of the original linguistic information.

Hesitant fuzzy linguistic term sets for linguistic decision making: Current developments, issues and challenges

The fuzzy linguistic approach is frequently considered as a solution for qualitative decision making. In the traditional framework of linguistic decision making, the representation of linguistic information is quite limited because the information has to be expressed by one predefined term. Hesitant fuzzy linguistic term sets (HFLTSs), which can be elicited by comparative linguistic expressions, have been proposed recently for the convenience of utilizing several consecutive terms at the same time and accommodating uncertainties and hesitations in human linguistic assessments. Since it was introduced, a large number of publications have been devoted to developing the theories, methods and applications of HFLTSs. In this paper, the concept and characteristics of HFLTSs are revisited at first and then the recent developments are reviewed and classified according to their computational strategies. Based on which, a comparative analysis of some similar techniques is presented to recognize the role of HFLTSs in linguistic decision making. Finally, some existing issues and current challenges are summarized to guide the prospective research of HFLTSs towards a high-quality progress.

Is Sign-only Forecast of Exchange Rate Easier than Forecasting Both Sign and Size?

Forecasting exchange rate movements is extremely difficult. While the usual forecast requires determining the size and sign of change, we investigate if the direction of change alone is easier to forecast. The accuracy rate of monthly forecasts based on an economic model is compared with random guessing that has the expected accuracy rate of 50%. Diebold-Marino test is used to see if the advantage of the economic model is statistically significant. We find that even a simple linear model based on UIP can predict the direction of change better than random guessing, even if the model’s performance is worse than random walk in terms of root mean squared error (RMSE) which is a widely used measure of the average size of the forecast errors, Binary response variable models such as logit and probit do not seem to improve the accuracy of directional forecasts. We also find that the forecast accuracy is quite sensitive to the in-sample size of rolling regressions and the treatment of the observations with no change. These findings indicate that sign-only forecasting may be a reliable tool for qualitative decision-making of a foreign exchange market dealer or an exporter interested in hedging exchange risk.

Extending Data Worth Analyses to Select Multiple Observations Targeting Multiple Forecasts.

Hydrological models are often set up to provide specific forecasts of interest. Owing to the inherent uncertainty in data used to derive model structure and used to constrain parameter variations, the model forecasts will be uncertain. Additional data collection is often performed to minimize this forecast uncertainty. Given our common financial restrictions, it is critical that we identify data with maximal information content with respect to forecast of interest. In practice, this often devolves to qualitative decisions based on expert opinion. However, there is no assurance that this will lead to optimal design, especially for complex hydrogeological problems. Specifically, these complexities include considerations of multiple forecasts, shared information among potential observations, information content of existing data, and the assumptions and simplifications underlying model construction. In the present study, we extend previous data worth analyses to include: simultaneous selection of multiple new measurements and consideration of multiple forecasts of interest. We show how the suggested approach can be used to optimize data collection. This can be used in a manner that suggests specific measurement sets or that produces probability maps indicating areas likely to be informative for specific forecasts. Moreover, we provide examples documenting that sequential measurement election approaches often lead to suboptimal designs and that estimates of data covariance should be included when selecting future measurement sets.

Discovering interdisciplinary interactions between two research fields using citation networks

As more and more interdisciplinary areas are emerging at a quick pace, analysis of interdisciplinary interactions among disciplines is of great importance. Citation network analysis is advancing as a tool to extricate policy implications from scientific as well as patent literature. Most of the studies related to interdisciplinarity under the lens of network analysis were concentrated mainly on journal–journal citation networks. Citation networks of articles reflect the accumulation as well as flow of knowledge. Therefore, specific developments that might cause interdisciplinary evolution can be identified. Due to this underexplored potential, we attempt to investigate interdisciplinarity at the level of published articles. As the interdisciplinary interactions among two disciplines is reflected by common/boundary papers and the arcs of cross-disciplinary citations, a quantitative methodology for assessing the strength of interdisciplinary interactions, dominant mode of interaction, mutual contribution, etc., is developed based on these. Interdisciplinary interactions among the fields ‘biotechnology for energy’ and ‘nanotechnology for energy’ is chosen as a case study. The existence of ‘mutual contribution’ among these fields is identified. ‘Biotechnology for energy’ is found to contribute more to the development of ‘nanotechnology for energy’ than vice versa. Important specific developments associated with interdisciplinary interactions are also explored using qualitative decision rules. Quantitative as well as qualitative methods devised in this paper form a framework for interdisciplinarity assessment that can be used by various decision makers.

English

New approaches and tools are needed to enable land tenancy arrangements in the developing countries to specify the landlord-tenant relationship in general and particularly in the targeted study area Khyber Pakhtunkhwa Pakistan. So this research work applied a multi-criteria decision making approach (MCDM) to investigate the important factors which greatly impact on initial signing process of land tenancy contracts between landlords and tenants by using Analytical Hierarchy Process (AHP) as a tool. This qualitative decision making technique has not been used extensively in the country especially in the landlord tenant relations. For the purpose field survey was conducted in August 2015 and interviewed 10 respondents (landlords and tenants) in a hypothetical situation from the baseline survey through a well-developed questionnaire by using Tones method in AHP. However, AHP is a methodology that facilitates respondents to trade off nonmarket factors of land tenancy contracts. Thus, the information was collected for the important factors (criterion) which has great effect in the initial contract agreement in the landlord-tenant relationship in our research area within each tenancy contract (alternative), then the important factors were incorporated in the AHP framework and subjected to the landlord-tenant judgments for each tenancy contract. The finalized factors were character, financial position, men power, experience, reference, land condition and house availability. The results of the AHP application to data collected from six different villages found that landlords’ preferences are strongest for character, men power in share cropping, distance, financial position in fixed contract, experience and men power in owner cultivation and the tenant’s partialities are strongest for house availability, financial position in share contract, land condition, reference in lease contract and in owner cultivation nothing found important. In overall, it was found that the dominant choice in the tenancy contract for landlords are share contract 45.7%, followed by rent contract 30.9% and less important owner cultivation 22.3% and in case of tenants it was found that the most preferable land tenancy contract is sharecropping 51.7% and fixed contract 41.7%, less effective 6.25% owner cultivation in the selected study villages. This study recommends that the agriculture and extension services departments of Khyber Pakhtunkhwa province to apply AHP as tool in the wide range of multi sector in agriculture decisions, such as to determine best allocation for farm production, adaptation of latest technological tools and choices among different food and cash crop. Key words: Analytical hierarchy process, Pakistan.

Attitudes and Practices of Homeowners in the Decision-making Process for Building Energy Renovation

The most recent studies point out that building users play a critical role in the decision-making process for the energy renovation of buildings as well as in energy use during the building life-time occupancy. Nevertheless, this important player has been poorly considered in the policies implemented. The homeowner, whose role has been passively induced to renovate accordingly with impositions of the regulations, is calling for himself a more active participation in the renovation process. The social dimension of the building renovation has been ignored. This study aims to highlight the role of the homeowner in the decision-making for energy building renovation investigating his motivations, needs, attitudes and daily routines. A selected group of Portuguese homeowners were interviewed. Also in Portugal, homeowners’ qualitative decisions and everyday life practices have a strong influence in the decision-making for building renovation.

Analyzing a Bipolar Decision Structure Through Qualitative Decision Theory

In this paper we study the link between a bipolar decision structure called BLF (bipolar leveled framework) and the qualitative decision theory based on possibility theory. A BLF defines the set of possible decision principles that may be used in order to evaluate the admissibility of a given candidate. A decision principle is a rule that relates some observations about the candidate to a given goal that the selection of this candidate may achieve or miss. The decision principles are ordered according to the importance of the goal they support. Oppositions to decision principles are also described in the BLF under the form of observations that contradict the realization of the decision principle. In order to show that this rich and visual framework is well founded we show how the notions defined in the BLF can be translated in terms of qualitative decision theory.

도시재생 사업추진과정에서의 의사결정기준 중요도 -청주시를 중심으로-

도시재생사업 추진과정에는 다양한 주체들이 참여하게 된다. 이에 따라 사업추진을 위한 의사결정 과정이 장시간 소요되고 많은 갈등이 유발될 수 있다. 이에 본 연구에서는 현재 추진 중이거나 추진 예정인 도시재생사업의 원활한 사업추진을 위한 중요 지표를 제시하고자 도시재생사업추진을 고려한 의사결정기준에 관한 중요도를 도출하였다. 본 연구에서는 도시재생사업이 추진 중인 지역의 추진주체들에 대한 설문조사 및 AHP 분석을 통하여 다음과 같은 분석결과를 도출하였다. 먼저 도시재생사업추진과정을 고려한 사업추진주체들의 의사결정기준 중요도를 분석한 결과 주민의견(0.393) > 지방자치단체 의지(0.231) > 전문가 의견(0.206) > 마스터플랜(0.169)의 순으로 중요도가 분석되었다. 다음으로 도시재생사업추진과정에서 사업참여자의 정성적 의사결정 기준에 관한 중요도를 분석한 결과 지속가능성(0.325) > 경제성(0.277) > 사업추진 용이성(0.232) > 형평성(0.166)의 순으로 중요도가 분석되었다. 끝으로 설문조사 과정에서 응답자를 도시재생사업 인지자와 미인지자 그룹, 도시재생사업지내 거주자와 사업지외 거주자 그룹으로 구분하여 보다 세부적인 분석을 실시한 결과, 일부 중요도 항목에서 의미 있는 차이점과 시사점이 도출되었다. 향후 본 연구의 성과가 도시재생사업의 성공적인 추진과 의미 있는 성과 도출을 위해 널리 활용되기를 기대한다. Urban regeneration projects involve various stakeholders, which result in decision making processes that require long periods of time and cause many conflicts. This study aims to identify important factors in decision making for promoting an urban regeneration project. The analysis results utilizing AHP are as follows: Firstly, the analysis results identify the main considerations in the process of promoting urban regeneration projects as residents' opinion(0.393), involvement of local government(0.231), opinions of related experts(0.206) and master plan(0.169). Secondly, the key drivers of stakeholders' qualitative decision making were found to include sustainability(0.325), economic feasibility(0.277), ease of project implementation(0.232) and equity(0.166). Lastly, meaningful differences in the relative importance of key aspects of decision making were identified when respondents were grouped according to being aware or not aware of the urban regeneration project, as well as living on or living off the project site. The results of this study can be used to implement successful urban regeneration projects in the future.

Environmental Reviews and Case Studies: Impacts on Maritime Cultural Resources: Assessing the Invisible

The management of developer-led pressures on the marine environment is archaeology's last frontier. Long inaccessible and invisible offshore, advances in technology have today propelled the sunken past into the consciousness of commercial archaeology. Arguably among no other form of heritage assets are archaeology and environment so complexly embedded. Lessons from the recent past have increasingly compelled developers to incorporate surveys of maritime seascapes into environmental impact assessments (coastal construction, sealane deepening, aggregate dredging, wind farms, and oil and gas pipeline and fiber-optic cable laying). Qualitative decisions about what to protect in situ, avoid, or excavate requires an objective understanding of significance assessment in relation to risk. The high profile of the United Nations Organization for Education, Science and Culture (UNESCO) Convention on the Protection of the Underwater Cultural Heritage exerts increasing pressures on governments worldwide to seek sustainable development. Demersal bottom fishing, World War II shipwreck hull oil leakage, and global warming are newly emerged risks that require expanded heritage recognition.

Studying of Innovative Qualities at Experts in the Field of Production and Use of Eco-Friendly Construction Materials

The modern industry lets out a huge amount of construction materials. Some of them have the limited sphere of use because of distinctions in technical, operational and ecological characteristics. Technological innovations in construction lead to creation of new materials and their introduction in construction production. Development of eco-friendly materials requires the high level of creativity. And commitment is necessary for introduction of this innovation in production and advances in the market. She allows to make the most qualitative and effective decisions on selection of materials. In the manuscript results of research of innovative qualities at the students studying "Production and use of construction materials" are stated. The increased level of innovative activity is revealed. Communication between innovative activity and creativity is confirmed. It is shown that too high creativity reduces commitment. Therefore when training students in the field of innovative materials for buildings and constructions, and first of all, eco-friendly materials, it is necessary to place emphasis on commitment development.

Stochastic flexible flow shop scheduling problem under quantitative and qualitative decision criteria

This paper addresses a bi-criteria stochastic flexible flow shop (SFFS) scheduling problem in which one criterion is quantitative and the other is qualitative. The quantitative criterion is the total weighted tardiness and the qualitative criterion is the importance of the customer for the company. To solve this problem, the integral analysis method (IAM), which consists of four stages (description of the problem, cardinal analysis, ordinal analysis and integration analysis), was used. The cardinal analysis implements both a mixed integral linear programming (MILP) model and a simulation-optimization approach for the total weighted tardiness solution. The ordinal analysis is performed by stochastic multicriteria acceptability analysis with ordinal data (SMAA-O) in which each alternative is qualified depending on customer importance. Finally, to address the integral analysis, deterministic SMAA is applied to select those alternatives that exhibited the best integral characteristics in terms of minimizing tardiness penalty costs and timely fulfillment of due dates according to customer strategic importance for the company. Results show that IAM enables selection of the alternatives that accomplish in the best way both types of criteria.

Approximating incompletely defined utility functions of qualitative multi-criteria modeling method DEX

Decision analysis is aimed at supporting people who make decisions in order to satisfy their needs and objectives. The method called DEX is a qualitative multi-criteria decision analysis approach that provides support to decision makers in evaluating and choosing decision alternatives by using discrete attributes and rule-based utility functions. In this work, we extend our previous efforts of approximating complete, monotone DEX utility functions with methods Direct marginals, UTADIS and Conjoint analysis to incompletely defined utility functions. The experiments are performed both on functions obtained by solving real world decision making problems and on artificially created ones. The results show that all three methods provide accurate approximations of incompletely defined DEX utility functions, when the evaluation is done only on rules present in these incompletely defined functions. Among the three methods, the Conjoint analysis method generally has the best performance, however it is closely followed by the Direct marginals method. The Conjoint analysis method also achieves a better performance in approximating fully defined DEX utility functions by using incompletely defined instances of those functions. The UTADIS method performs comparatively well with functions having a high percentage of missing values.

Forecasting Stock Price using Wavelet Neural Network Optimized by Directed Artificial Bee Colony Algorithm

Stock prediction with data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. This study proposes an integrated approach where Haar wavelet transform and Artificial Neural Network optimized by Directed Artificial Bee Colony algorithm are combined for the stock price prediction. The proposed approach was tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the prediction result was found satisfactorily enough as a guide for traders and investors in making qualitative decisions.

Methodological Aspects of Qualitative-Quantitative Analysis of Decision-Making Processes

Abstract The paper aims at recognizing the possibilities and perspectives of application of qualitative-quantitative research methodology in the field of economics, with a special focus on production engineering management processes. The main goal of the research is to define the methods that would extend the research apparatus of economists and managers by tools that allow the inclusion of qualitative determinants into quantitative analysis. Such approach is justified by qualitative character of many determinants of economic occurrences. At the same time quantitative approach seems to be predominant in production engineering management, although methods of transposition of qualitative decision criteria can be found in literature. Nevertheless, international economics and management could profit from a mixed methodology, incorporating both types of determinants into joint decision-making models. The research methodology consists of literature review and own analysis of applicability of mixed qualitative-quantitative methods for managerial decision-making. The expected outcome of the research is to find which methods should be applied to include qualitative-quantitative analysis into multicriteria decision-making models in the fields of economics, with a special regard to production engineering management.