Software development with minimum effort has become a challenging task for the software de-velopers. Software effort may be defined as the prediction process of the effort required to de-velop any software. Many software effort estimation models have been developed in the past, but it is observed that none of them can be applied successfully in all kinds of projects in differ-ent environments that raise the problem of the software effort estimation model selection. To se-lect the suitable software effort estimation model, many conflicting selection criteria must be con-sidered in the decision process. The present study emphasizes on the development of a fuzzy multi-criteria decision making approach by integrating Fuzzy Set Theory and Weighted Distance Based Approximation. To show the consistency of the proposed approach, methodology valida-tion is also performed by making comparison with existing methodologies and to check the criti-cality of the selection criterion, sensitivity analysis is also performed.
In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.
Selection of the qualified and the most appropriate employee plays crucial role for the success of the businesses. The selection process is complex and contains both subjective and objective criteria to be considered. For this reason, in this paper, Grey Relational Analysis (GRA) is proposed for employee selection. To illustrate the applicability of the proposed method, the most appropriate software engineer is selected for a technology firm. By this way, a scientific multi criteria decision making (MCDM) method is proposed to the firm that determines the best candidate intuitively with traditional methods.
Developing innovation, based on knowledge and technology, as a driving force of the economy, is necessary for survival and is required in having strong interactions within the globalized world of business. Innovation and technology development require an intertwined network of organizational interactions between public and private sector. The activities and interactions of these firms are the reasons for innovation development in the framework of innovation systems. Following strategies is of crucial necessity and importance in industries such as aerospace and remotely-piloted helicopters (RPH) with their complex characteristics, costly and time-consuming processes. Understanding the business environment and identifying the success factors is a significant step towards adopting innovative strategies and planning for technology development. The aim of this article is to evaluate the key success factors in technological innovation development of remotely-piloted helicopters (RPH) industry. The methodology used in this article is Best-Worst method which is considered as one of the most prominent and effective MCDM methods. Based on a case study and by reviewing the extant and relevant literature, the key success factors of technological innovation development of remotely-piloted helicopters (RPH) industry in Iran were identified. Then by applying the “Best-Worst” method and the experts’ opinions, the key success factors were analyzed and prioritized. Finally, some suggestions are made by considering the results of the study.
This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM) methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment) and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis) which are integrated through group decision making (GDM) method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.
This paper is about creating a hybrid QFD-based approach in which the best supplier is selected considering changing customer needs. In most previous studies employing a QFD approach, the possibility of changing customer needs is ignored. On the other hand, supplier selection is a challenging problem that could have been addressed by such a QFD. This paper attempts to create a hybrid QFD-based approach in which the internal relations between the elements are considered. It connects the new QFD to suppliers’ qualifications to create a hybrid supplier selection process. The best suppliers are selected based on the priorities of customer needs for each level of the product improvement plan. When a product is to be developed, the proposed methodology seems to create an efficient solution for supplier selection problem with respect to quality factors.
The selection of air compressor is a Multiple Criteria Decision Making (MCDM) problem including conflicting criteria and various alternatives. Selecting the appropriate air compressor is an important decision for the company as it affects the energy consumption and operating cost. To aid the decision making process in the companies, MCDM methods are proposed in the literature. In all MCDM methods, the main goal is to select the best alternative or to rank a set of given alternatives. In this paper, the air compressor is selected for a spinning mill of a textile company with an integrated approach based on MACBETH (Measuring Attractiveness by a Categorical Based Evaluation TecHnique) and COPRAS (COmplex PRoportional ASsessment) methods. MACBETH method is utilized to determine the weights of the criteria. Then COPRAS method is used to determine the ranking of the alternatives and select the best one.
Supplier selection management has been considered as an important subject for industrial organizations. In order to remain on the market, to gain profitability and to retain competitive advantage, business units need to establish an integrated and structured supplier selection system. In addition, environmental protection problems have been big solicitudes for organizations to consider green approach in supplier selection problem. However, finding proper suppliers involves several variables and it is critically a complex process. In this paper, the main attention is focused on finding the right supplier based on fuzzy multi criteria decision making (MCDM) process. The weights of criteria are calculated by analytical hierarchical process (AHP) and the final ranking is achieved by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). TOPSIS advantage among the other similar methods is to obtain the best solution close to ideal solution. The paper attempts to express better understanding by an example of an automobile manufacturing supply chain.
Wind farms are designed to supply power to the consumers at a minimal price. The cost of wind power production directly or indirectly depends on proper selection of vendors. The present paper highlights a model for selection and ranking of vendors for a wind farm based on fuzzy set theory to determine criteria weights and an additive ratio assessment (ARAS) method to analysis criteria values. The objective of the paper is to establish the ARAS method as an effective method for Vendor selection. A case study is shown to ascertain the proposed method especially when the criteria are interdependent and conflicting in nature. The result is validated with another popular MCDM technique, COPRAS, which shows that the models are effective and applicable, and provide decision makers with better solutions for decision making.
Human resource management plays an essential role on development of any business organization. Selection of employee normally depends on various criteria such as employee commitment, necessary skills, etc. Therefore, a good strategy to hire appropriate employee is a multi-criteria decision making (MCDM) specially the ones, which could handle uncertainty, properly. In this paper, we present a method to use MCDM techniques for hiring employees. In fact, the present work proposes a Fuzzy Analytic Hierarchy Process (FAHP) as one of the most popular multi-criteria decision making techniques. A computer application is developed where it receives the configuration of the employee selection problem, evaluates the candidates and ranks them using the appropriate voting system.