Automated Hybrid Methodology for Software Architecture Style Selection Using Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process

Selecting process of a machine tool has been very important issue for companies for years, because the improper selection of a machine tool might cause of many problems affecting negatively on productivity, precision, flexibility and company’s responsive manufacturing capabilities. On the other hand, selecting the best machine tool from its increasing number of existing alternatives in market are multiple-criteria decision making (MCDM) problem in the presence of many quantitative and qualitative attributes. Therefore, in this paper, an analytic hierarchy process (AHP) is used for machine tool selection problem due to the fact that it has been widely used in evaluating various kinds of MCDM problems in both academic researches and practices. However, due to the vagueness and uncertainty on judgments of the decision-maker(s), the crisp pair wise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). That is why; fuzzy number logic is introduced in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP. Shortly, in this study, an intelligent approach is proposed, where both techniques; fuzzy logic and AHP are come together, referred to as fuzzy AHP. First, the fuzzy AHP technique is used to weight the alternatives under multiple attributes; second Benefit/Cost (B/C) ratio analysis is carried out by using both the fuzzy AHP score and procurement cost, of each alternative. The alternative with highest B/C ratio is found out and called as the ultimate machine tool among others. In addition, a case study is also presented to make this approach more understandable for a decision-maker(s).

Purpose Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey. Design/methodology/approach In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA. Findings The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management. Research limitations/implications In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives. Practical implications In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors. Social implications On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world. Originality/value On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem.

This paper aims to develop an effective and efficient hybrid normalised multi criteria decision making model for evaluating and selecting the vendor using an Analytical Hierarchy Process (AHP) and Fuzzy Analytical Hierarchy Process (FAHP) and an integrated approach of Grey Relational Analysis (GRA) in a Supply Chain Model (SCM). The first part of the model deals with the selection of vendor using AHP and FAHP. The second part of the model deals with a hybrid approach of AHP along with GRA and FAHP along with GRA. This paper demonstrates how the model can help in solving such decisions in practice. The effectiveness of the hybrid model is illustrated using a case study taken in paper manufacturing industry located in southern part of India and validated the results of hybrid model using the result obtained from AHP and FAHP. The proposed model helps the industry to effectively select the vendor.

Material selection is one of the most predominant activities in design process. In a successful product design, selection of material plays a vital role. As various alternatives are available, selecting the best among them which satisfies the manufacturer's requirement becomes more complex and time consuming. To choose an appropriate material with several criterion is a multi-objective task and it is a multi criteria decision making (MCDM) problem. This paper encompasses the use of preference ranking organisation method for enrichment evaluation (PROMETHEE) integrated with analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (FAHP) for the successful material selection. The FAHP and AHP are used to identify the criterion weight and PROMETHEE II is employed to rank alternatives. In this work, seven attributes and five stainless steel grades are focussed for optimised selection. The obtained results are contrasted to show the effectiveness of FAHP over the traditional AHP.

Shipping logistics is one of the very important criteria which can directly and indirectly affect the economy and GDP of any country. Shipping logistics depends on various factors which have been addressed by several authors in their previous studies. Studies in this literature are focused on selecting the most impactful factors among all the criteria. Methods used in this literature are fuzzy Analytical hierarchy process (AHP) and fuzzy Technique for order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria decision analysis. These methods also helped in this literature to develop a new hybrid method “fuzzy TOPSIS AHP”. There have been no studies involving maritime logistics with comparative analysis of multi-criteria decision making i.e., fuzzy AHP and fuzzy TOPSIS AHP. The literature involved large number of expert opinions on the factor prioritization of maritime logistics. Factors selected for prioritization are Environmental Sustainability, Supply and Demand, Operations and Port Selection. However, the research showed that the comparative analysis of the results was quite opposite to one another and proposed a new way for researchers to use the hybrid method of fuzzy TOPSIS AHP method in future research. The study aimed to improve the existing maritime model which can help professionals to get connected with the maritime logistics firms. The study also aims to contribute this model for researchers in their study related to maritime logistics.

Every complex problem now days require multicriteria decision making to get to the desired solution. Numerous Multi-criteria decision making (MCDM) approaches have evolved over recent time to accommodate various application areas and have been recently explored as alternative to solve complex software engineering problems. Most widely used approach is Analytic Hierarchy Process that combines mathematics and expert judgment. Analytic Hierarchy Process suffers from the problem of imprecision and subjectivity. This paper proposes to use Fuzzy AHP (FAHP) instead of traditional AHP method. The usage of FAHP helps decision makers to make better choices both in relation to tangible criteria and intangible criteria. The paper provides a clear guide on how FAHP can be applied, particularly in the software engineering area in specific situations. The conclusion of this study would help and motivate practitioners and researchers to use multi-criteria decision making approaches in the area of software engineering.

Entscheiden bei unschärfe — Fuzzy decision support systeme: Springer-Verlag, Berlin, 1988, ix + 304 pages, DM45.00

Effects of increasing fuzziness on analytic hierarchy process for spatial multicriteria decision analysis

  The selection of the appropriate combination of materials for a manufacturing company is one of the important points to achieving high competitiveness in the market. Besides, an appropriate choice of materials is very important as it helps to reach optimum production rate and efficiency. Today’s market offers many more choices for materials alternatives. There are also many factors one should consider as part of the appropriate combination of materials selection process, including productivity, wastage, cost, style, etc., consequently, evaluation procedures involve several objectives and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For dealing with these problems, multiple criteria decision making (MCDM) has been found to be a useful approach to solve this kind of problem. Most of the MCDM models are basically mathematical and disregard qualitative and subjective considerations. The application of fuzzy set theory allows incorporating the vague and imprecise linguistic terms and qualitative information into the decision process. This paper devises a fuzzy hybrid analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach to the problem of thesis subject selection. Fuzzy AHP is used to formulate and calculate the weight of each criterion, and fuzzy TOPSIS is proposed to prioritize combination material alternatives from the best to the worst ones. A case study on Kaach Company was put forward to illustrate the performance of the proposed methodology.   Key words: Combination of material, material selection, fuzzy analytical hierarchy process (AHP), fuzzy technique for order preference by similarity to ideal solution (TOPSIS).

Cash crops, which include eucalyptus, play an important role in Thailand in wood utilization. Consequently, cash crops have become a significant driving force in land use changes and low crop yield; thus, the development of an accurate cash crop suitability model is needed. The aim of this study is to evaluate the land suitability of cash crops, such as eucalyptus, which is based on Multi Criteria Decision Making (MCDM) in Nakhon Ratchasima Province in Thailand. Parametric, classical Analytical Hierarchy Process (AHP), and fuzzy AHP (FAHP) approaches integrated with Geographic Information Systems (GIS) are compared to accomplish this. Parametric approaches equally allocate importance to all factors. AHP assigns the distribution of important factors using expert opinions. FAHP accounts for the uncertainty in expert opinions, and the triangular (Tri) and trapezoidal (Tra) approaches are compared. The results demonstrated that Trapezoidal Fuzzy AHP (TraFAHP) could classify and map cash crop suitability with 90.16% accuracy, which is a higher overall accuracy than the other approaches that are based on reference map validation. Therefore, we recommend the TraFAHP method for accurately identifying cash crop suitability.

This chapter presents a review on risk assessment methodologies that incorporate fuzzy analytic hierarchy process (FAHP). We classify FAHP applications from the Institute for Scientific Information (ISI) Web of Knowledge database into two main categories: fuzzy singular analytic hierarchy process and fuzzy hybrid analytic hierarchy process. We considered five criteria in our taxonomy: (1) Did the study perform group decision-making? (2) Did the study differentiate each decision maker's competence according to their background and experience? (3) Did the study model the decision maker's risk attitude? (4) Did the study perform sensitivity analysis? (5) Did the study validate the proposed model? The studies are then grouped into four explanatory fields: (1) year of publication, (2) type of FAHP application, (3) main objective of the FAHP application, and (4) some observations based on the outcome of the abovementioned taxonomy analyses. In this stage, the information is summarized and depicted in appropriate tabular formats and graphical charts for a quick interpretation on review trends. Some managerial insights are then provided. Pragmatically, this work serves as a guide to researchers who are seeking for research gaps in the area of risk assessment and FAHP models.

ABSTRACTThe selection process for the best computer-aided manufacturing (CAM) software among a set of potential number of alternatives in market has been critical issue for most companies that aim to make their design/manufacturing-related activities automated. Because this selection process is very vital for companies because a wrong decision might put them into a difficult position in terms of economical, market share and time spent. Therefore, today’s companies have used different multiple-criteria decision making (MCDM) methods for the evaluation study of CAM software alternatives to make this complex process easily applicable and not time-consuming. Among the MCDM methods in literature, the analytic hierarchy process (AHP) method has been widely used for various MCDM problems in both academic researches and industrial practices. However, in some cases, because of the vagueness and uncertainty on the judgments of decision maker(s), the crisp pair wise comparison in the conventional AHP seems to be insufficient and imprecise to capture the right judgments of decision maker(s). Therefore, a fuzzy logic method is integrated in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP, called as fuzzy AHP. Moreover, the proposed approach is also realized on a case study.

In the area of Multi Criteria Decision Making, it is well known that Analytical Hierarchy Process (AHP) is widely used. In the AHP, the weight of criteria and alternatives are obtained from the expert judgment doing pairwise comparison. Fuzzy AHP (FAHP) is developed in order to overcome situation in which expert has difficulty to give clear judgment on the comparison. FAHP is usually developed using a set of Triangular Fuzzy Number (TFN). This research is proposed a FAHP with unconventional TFN, which allow the expert give his/her own fuzzy number for each comparison. We name the number as the Unsymmetrical Triangular Fuzzy Number, in which the membership function is still in the shape of triangular but the shape is not symmetric. The complete methodology of the proposed FAHP is developed with reference to the fuzzy logarithmic least square method (LLSM). A case study for supplier selection process is provided in order to show the applicability of the proposed method.

Rapid identification of groundwater sources is crucial for emergency water supplies. Yudu County (YDC) in Southern China serves as a case study due to its typical mountainous terrain and pressing groundwater demands. To address the limitations of conventional groundwater mapping methods in large-scale areas with sparse data, this study integrates remote sensing (RS), geographic information systems (GIS), and multi-criteria decision analysis (MCDA) techniques to delineate groundwater potential zones (GWPZs) in YDC. Following a series of correlation tests, seven assessment indicators were selected from various groundwater influencing factors, including two innovative ones: terrestrial water storage change (TWSC) and spring flow. The analytic hierarchy process (AHP) and fuzzy AHP (FAHP) models were employed to calculate factor weights, and GWPZ maps were generated using weighted overlay analysis in GIS. The model performance was validated using borewell data, receiver operating characteristic (ROC) curves, and yield prediction models. Additionally, four water enrichment types and their spatial distribution were identified by field investigations and yield prediction assessments. Results indicated a remarkable similarity between GWPZs delineated by AHP and FAHP, categorized into five classes: very high (13.92% for AHP and 14.33% for FAHP), high (26.29 and 27.55%), medium (29.33 and 28.14%), low (20.66 and 21.50%), and very low (9.80 and 8.48%). The area under the curve (AUC) for FAHP was 85.09%, slightly higher than the 84.41% of AHP, while the correlation coefficient (R2 of the prediction model improved from 0.747 to 0.817 with FAHP. These findings confirmed the reliability of combining GIS and MCDA methods to delineate GWPZs, with FAHP demonstrating an advantage over AHP. The proposed methodology and resulting mapping significantly enhance sustainable water resource management and development in YDC, offering a practical framework for rapid groundwater investigations in disaster response, as well as for long-term water security planning in similar mountainous environments.

Multi-attribute decision making (MADM) is a state-of-the-art, popular technique for dealing with real-world problems. An effective decision can be made for various real-world problems involving multiple attributes to decide a proper solution. Software testing and bug fixing are essential steps in the field of software engineering. Bug triaging is a real challenge in large-scale software development. Bug triaging is the process of allocating newly reported bugs to the best developer who meets the requirements for addressing them. In this paper, a software developer ranking model based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed for an effective bug triaging process. Developers are ranked based on various criteria using the TOPSIS model for effective bug triaging. Assigning newly reported bugs to the appropriate and available software developer is a complex decision-making process. It involves consideration of multiple criteria for discovering the optimal solution. In software engineering, bug triaging refers to the process of allocating appropriate developers to a newly reported bug. This paper presents criteria for finding suitable developers using multi-criteria decision-making (MCDM) techniques. The Analytic Hierarchy Process (AHP) method is used to determine the weights of the criteria, and the TOPSIS MCDM technique is used to rank the most appropriate developer.