Integrating TOPSIS and AHP into GORE Decision Support System

International Journal of Advanced Computer Science and Applications, 2016

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.

Mathematical and Computer Modelling, 1988

Multiple Criteria Decision Making, International Scientific Journal issued by the University of Economics in Katowice, Poland, 2019

Decision-making in the field of information systems has become more complex due to larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly uncertain environment. Software systems play unique roles in the translation of corporate strategic and tactical plans into actions. We present the results of a study designed to develop and evaluate an Analytical Hierarchy Process (AHP) model to support decision making in the selection of appropriate software system to meet organizational needs. Our results show the viability of the AHP methodology in software system/project selection, and points to the importance of functionality (35.26%), quality (22.00%) and usability (19.34%) criteria in the overall decision process. Cost and vendor service did not seem to exert significant weight in the decision matrix.

International Journal of Information Technology and Computer Science, 2018

Requirements prioritization is an essential component of software release planning and requirement engineering. In requirement engineering the requirements are arranged as per their priority using prioritization techniques to develop high-quality software's. It also helps to the decision makers for making good decisions about, which set of requirements should be executed first. In any software development industry a 'software project' may have a larger number of requirements and then it is very difficult to prioritize such type of larger number of requirements as per their priority when stakeholder's priorities are in the form of linguistic variables. This paper presents a comparative analysis of existing seven techniques based on various aspects like: scale of prioritization, scalability, time complexity, easy to use, accuracy, and decision making, etc. It was found from literature survey none of the techniques can be considered as the best one. These techniques undergo from a number of drawbacks like: time complexity, lack of scalability, Negative degree of membership function, inconsistency ratio, rank updates during requirement development, and conflicts among stakeholders. This paper proposed a model called 'ANN Fuzzy AHP model' for requirements prioritization that will overcome these limitations and drawbacks. In the investigation of this proposed model, a case study is implemented. Ozcan et al [31] using a FAHP (Fuzzy AHP) with ANN based technique to choose the best supplier based on the multiple criteria. The examination on ANN with FAHP is performed on MATLAB software and outcome evaluated by fuzzy pairwise comparison matrix with three supplier selection criteria states that the requirements prioritization outcome is better from existing techniques.with higher priority.

2021

Prioritizing software requirements is one of the most significant and complex tasks for software developers. It involves a multi-criteria decision process to balance the benefit of each requirement and its cost, considering different factors and dimensions, many of which are qualitative. Although numerous prioritization methods have been developed to date, the appropriate treatment in cases of the uncertainty and indeterminacy inherent in human decisions is limited. In the present work, the neutrosophic TOPSIS is proposed as a method of prioritizing requirements. This multi-criteria and multi-expert method uses linguistic terms associated with Single Value Neutrosophic Sets and allows the inclusion of aspects such as the importance of the criteria and the weight of expert evaluations. A case study is used to show the applicability of the proposal.

2020

Everyone makes decisions almost daily about routine purchases. When different items (e.g bread, milk) provide the same quality and quantity then potentially, the purchase decision is based on monetary grounds. However, when the additional criteria like quantity, quality, etc, change, such a situation demands activation of a simplistic form of multi-criteria analysis which is performed by our brain. However, when the purchases are non-routine and have multi-criteria then those become complex which prompts us to consult our friends and sometimes the relevant specialist persons for good guidance. One such example may be a decision to buy a car which in addition to the capital cost, more parameters come into play like fuel economy, availability of spare parts, operation and maintenance cost, safety, and others. The above two situations generally don’t demand any kind of analytical or other processes to address its complexity, however, projects of commercial or communal interest do demand such where conflicts in terms of individual subjectivity surface. To address the subjectivities, Mathematicians and Statisticians have developed various tools and processes. Multi-Criteria Decision Analysis (MCDA) is a sub discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (Multiple-criteria decision analysis, 2020). The Analytic Hierarchy Process (AHP) is a general theory of measurement that has found its widest applications in multi-criteria decision making, planning, and resource allocation, and in conflict resolution (Saatay, 1987). The AHP method makes it possible to assign a value representing the preference degree for a given alternative to each additional alternative. Such values can be used to classify and select alternatives based on a hierarchical structure (Junyi Chai, August 2013). AHP is the most widely used method for evaluating software (Ashu Gupta, 2010). AHP has also been applied to supplier and vendor selection (Maggie C.Y. Tam, April 2001). Recent approaches have combined AHP with other methods (Ahn, March 2017). AHP helps capture both subjective and objective evaluation measures, providing a useful mechanism for checking their consistency relative to considered alternatives, thus reducing bias in decision making (Mann, 1995). The weighting values in the AHP, which reflect the status or role of various factors in the evaluation process, directly affect the decision-making results (S. Prechaverakul, 1995). Consultation is the first step toward designing, execution, and operation of a sustainable project. The same help in conflict resolution, conducting trade-offs, and bringing in objectivity. AHP helps to smoothen the whole process by taking away personal subjectivities. The process is observable and without manipulation but there is an intrinsic challenge. Which is that why a certain weightage is assigned to the component, and its factors and sub-factors? This in-built flaw has derived a considerable amount of objection to it (MCDA or AHP methods for different alternatives, 2020). Given its flaw, it is still a good process and widely used by many professionals across the globe. MCDA is a family of methods whereas AHP is one of the approaches to address the method (MCDA or AHP methods for different alternatives, 2020). In this approach, the following steps are required to successfully conclude the effort (Asim, 2020); 1. Clearly defining the objective 2. Defining criteria for success 3. Assigning weights to criteria and its factors and sub-factors 4. Listing all the potential project options 5. The rating according to a pre-defined scale in a group for more objectivity. I prefer the Likert Scale. 6. Calculate and rank

International Journal of Engineering Research & Technology (IJERT), 2022

Several software packages are available for the smooth-running of an educational system. However, making the choice for most-appropriate software can be very tasking. This may require the meeting of the school's management team to take quality decisions based on some given criteria. As a result, conflicts may arise if standard multicriteria decision methods are not applied in the selection process. This current research focuses on the application of AHP and TOPSIS methods to select the most relevant software among three options for use in a high school. Five members of the management team evaluated the various criteria and conducted pair-wise comparisons to determine the weights using AHP. The choices were further ranked based on the TOPSIS method. The result showed SMS C as the best choice for the school, with a TOPSIS ranking score of 0.730044.

International Journal of Physical Distribution & Logistics Management, 1992

With increasingly complex logistics information technology and dynamic logistics operations in a global setting, today′s logistics managers confront an overwhelming number of decision alternatives. Perhaps the most effective way of evaluating such a large number of alternatives is to utilize advanced information technologies. These technologies encompass decision support systems (DSS), artificial intelligence (AI), expert systems (ES), electronic data interchange (EDI), and barcoding. Since the performance of these technologies is greatly influenced by their supporting software, their success often hinges on the selection of proper software packages. In selecting proper logistics software, an analytic hierarchy process (AHP) is proposed which can effectively deal with both qualitative and quantitative factors in multiple‐criteria decision environments.

International Journal of Advanced Computer Science and Applications

One of the main activities of software requirements analysis is requirements prioritization. The wrong requirements prioritization is risky as it leads to many software failures. The current requirements prioritization techniques can't deal with large requirement numbers efficiently, which is considered one of their main issues. Many researchers have agreed that the analytical hierarchy process (AHP) is one of the best prioritization techniques as it produces highly accurate results. AHP has two main problems: scalability and inconsistency. These problems have motivated us to propose an improved version of AHP for software requirements prioritization, namely Enhanced AHP (E-AHP). A performance evaluation has been done for the conventional AHP, E-AHP, and one of the recent algorithms that also try to solve the AHP scalability problems, namely removing eigenvalues and introducing the dynamic consistency checking algorithm into AHP (ReDCCahp) algorithms The evaluation shows which algorithm takes the least time, uses the least memory, produces the most consistent and accurate results, and has the highest scalability. The three algorithms have been evaluated by running their codes using different numbers of requirements ranging from 10 to 500. The results show that E-AHP is more scalable, takes the least time, uses the least memory, and produces the most consistent and accurate results compared to the other two algorithms. That becomes remarkable when the number of requirements increases. Therefore, E-AHP is suitable to be applied in large software projects, as it can deal efficiently with the large software requirements numbers.

2007

Requirements prioritization aims at identifying the most important requirements for a system (or a release). A large number of approaches have been proposed so far, to help decision makers in performing this activity. Some of them provide supporting tools. Questions on when a prioritization technique should be preferred to another one as well as on how to characterize and measure their properties arise. Several empirical studies have been conducted to analyze characteristics of the available approaches, but their results are often difficult to compare.