Next generation wireless networks will integrate various heterogeneous technologies like WLAN, WiMax and cellular technologies etc., to support multimedia services with higher bandwidth and guaranteed quality of service (QoS). In order to keep the mobile user always connected to the best wireless network in terms of QoS parameters and user preferences, an optimal network selection technique in heterogeneous networks is required. This paper proposes a novel fuzzy-Analytic Hierarchy Process (AHP) based network selection in heterogeneous wireless networks. Triangular fuzzy numbers are used to represent the elements in the comparison matrices for voice, video and best effort applications. Deriving crisp weights from these fuzzy comparison matrices is a challenging task. When extent analysis method is applied, irrational zero weights are obtained for some attributes. Due to this, many important criteria are not considered in the decision making process. To overcome this problem, a new non-linear fuzzy optimization model for deriving crisp weights from fuzzy comparison matrices for network selection is presented. The weights obtained from this model are more consistent than the existing optimization models. Also, parameterized utility functions are used to model the different Quality of Service (QoS) attributes (bandwidth, delay, jitter, bit error rate) and user preferences (cost) for three different types of applications. Finally, scores are calculated exclusively for each network by three MADM (Multiple Attribute Decision Making) methods Simple Additive Weighting (SAW), TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) and MEW (Multiplicative Exponential Weighting). Results show that the MEW method gives more appropriate scores with utility functions than the SAW and TOPSIS methods. © 2017 Elsevier B.V.

Arun Kumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Goyal R.K

Kaushal S

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Applied Soft Computing

Lecture Notes on Multidisciplinary Industrial Engineering Trends in Manufacturing Processes

Experimental and Numerical Procedure for Studying Effect of Ultrasonic Spot Weld Parameters on Metal Joints for Electronic Components

Adopting the multidimensional balanced scorecard approach to improve project management and organizational performance can help reduce project risks and potential disasters in order to maximize the investment benefits and security of IT projects with high risks. We adopted the stimulus-organism-response (S-O-R) research context, whose stimulus, organism, and response refer to project risk, project management, and organizational performance, respectively. Furthermore, a questionnaire survey of project management experts was conducted. We then utilized the DANP model, which combines the Decision-Making Trial Evaluation Laboratory (DEMATEL) and the analytical network process, to explore the relationships among project risks, project management, and organizational performance. We observed the following: (a) effective project management can reduce project risk and improve organizational performance; (b) project risk is most influenced by the user; (c) senior manager support significantly influences project management; (d) organizational learning and growth has a significant impact on organizational performance; and (e) the criteria with the largest relative weight is generally considered to pose a risk, which indicates that the experts seriously consider that project risk. Our results can provide a valuable reference for project management to reduce risk and improve organizational performance. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

Journal of Ambient Intelligence and Humanized Computing

A study for project risk management using an advanced MCDM-based DEMATEL-ANP approach

Purpose: Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is one of the most commonly used techniques for strategic planning. SWOT examines the strengths (S) and weaknesses (W) agents of the community together with opportunities (O) and threats (T), for selecting and implementing the best strategy which helps in achieving its goals. The purpose of this paper is to enhance the performance of SWOT analysis regarding the quantitative side of strategies, select the best strategy from different strategies and deal effectively with vague and incompatible information, which occurs usually in actual life. Design/methodology/approach: This study used the neutrosophic analytic hierarchy process (AHP) incorporated with SWOT analysis. Findings: By adding the neutrosophic AHP to SWOT analysis, the performance of SWOT analysis is enhanced through determining the quantitative values and dealing with vague and inconsistent information effectively leading to improved decisions. Research limitations/implications: The developed integrated methodology is validated in a real-life case of Starbucks company. For the case study of Starbucks company, the proposed model helps in determining different strategic plans and, further, ranking these plans effectively, which will help the company to compete with its competitors and develop itself by obtaining a competitive advantage over its competitors in an uncertain business environment. Practical implications: In the case study of Starbucks company, the proposed model helps to determine the different strategic plans, rank these plans which help the company compete with its competitors, develop itself and grow. Originality/value: This research is the first to address SWOT analysis with neutrosophic AHP. © 2018, Emerald Publishing Limited.

Benchmarking: An International Journal

An integrated neutrosophic AHP and SWOT method for strategic planning methodology selection

The utility based non-linear fuzzy AHP optimization model for network selection in heterogeneous wireless networks

Internet of Things (IoT) is a heterogeneous ubiquitous network based upon modern computational intelligent techniques. A large scale IoT environment composed of thousands distributed entities and a number of multimedia smart devices. In recent years, due to the improvement of popularity and capability of smart mobile devices, Mobile Cloud Computing (MCC) gains a considerable attention in Internet of Things (IoT) environment. As there are variety of clouds that provides same services, it becomes quite difficult for users to choose an ideal cloud from a variety of clouds for migrating computationally intensive applications. So, selecting the optimal cloud among multiple alternatives which saves resource availability and execution time is a Multi-Criteria Decision Making (MCDM) issue. This chapter introduces an assessment model based on Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) which helps the users to select an optimal cloud where uncertainty and subjectivity are parameterized using triangular fuzzy members and is handled by using linguistic values. The proposed computational intelligence decision making model enables decision makers to better understand the whole evaluation process and thus provides more accuracy, systematic and efficient decision support tool. © Springer International Publishing AG 2018.

Cognitive Computing for Big Data Systems Over IoT Lecture Notes on Data Engineering and Communications Technologies

Modelling and Analysis of Multi-objective Service Selection Scheme in IoT-Cloud Environment

Supplier selection is one of the key activities of purchase management in supply chain. Supplier selection is a multifaceted problem relating qualitative and quantitative multi-criteria. This paper deals with a supplier selection problem in an Indian automobile company. The work presents selection of headlamp supplier using integrated fuzzy multi-criteria decision-making approaches: analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The selection process starts with identifying the criteria based on literature review and interviewing industry experts. Weights to criteria are assigned using AHP, and suppliers are ranked using AHP and TOPSIS. Consistency tests are carried out to check the quality of expert’s inputs. Also, sensitivity analysis is done to check the robustness of the approach. The results address that fuzzy approaches could be effective and more accurate than the existing approaches for supplier selection problems. © 2016, The Natural Computing Applications Forum.

Neural Computing and Applications

Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry

The offshore/on-site teams’ knowledge transfer effectiveness is one of the key predictors for evaluating the outcome of global software development (GSD) project. This study aims at proposing an assessment framework that can be used to evaluate the GSD teams’ (offshore/on-site) knowledge transfer effectiveness in the following criteria: knowledge, team, technology, and organization factors. For evaluating the teams’ knowledge transfer effectiveness in GSD projects, we have integrated the fuzzy decision making trial and evaluation laboratory (DEMATEL) and fuzzy multi-criteria decision making (FMCDM) approaches. Moreover, the proposed DEMATEL-FMCDM methodology is used to determine priority weights of each evaluation criterion and rate knowledge transfer effectiveness on the GSD project outcome from software service outsourcing perspective into two dimensions: product success, (schedule, cost improvement, etc.) and service quality (personal satisfaction, and successful collaboration). The proposed methodology is used for the prediction of a possible rating mechanism for determining the GSD project outcome through knowledge transfer criterions of GSD teams. It also facilitates the determination of knowledge transfer effectiveness of GSD teams’ towards the success of the GSD project outcome and initiates actions to improve the project outcome in GSD environment. This study demonstrates a survey research method that addresses 35 knowledge transfer factors assessed by 70 software professionals at Inowits software organization in India.

International Journal of Machine Learning and Cybernetics

Integration of fuzzy DEMATEL and FMCDM approach for evaluating knowledge transfer effectiveness with reference to GSD project outcome

Heart failure (HF) has been considered as one of the deadliest human diseases worldwide and the accurate prediction of HF risks would be vital for HF prevention and treatment. To predict HF risks, decision support systems based on artificial neural networks (ANN) have been widely proposed in previous studies. Generally, these existing ANN-based systems usually assumed that HF attributes have equal risk contribution to the HF diagnosis. However, several previous investigations have shown that the risk contributions of the attributes would be different. Thus the equal risk assumption concept associated with existing ANN methods would not properly reflect the diagnosis status of HF patients. In this study, the commonly used 13 HF attributes were considered and their contributions were determined by an experienced cardiac clinician. And Fuzzy analytic hierarchy process (Fuzzy_AHP) technique was used to compute the global weights for the attributes based on their individual contribution. Then the global weights that represent the contributions of the attributes were applied to train an ANN classifier for the prediction of HF risks in patients. The performance of the newly proposed decision support system based on the integration of ANN and Fuzzy_AHP methods was evaluated by using online clinical dataset of 297 HF patients and compared with that of the conventional ANN method. Our result shows that the proposed method could achieve an average prediction accuracy of 91.10%, which is 4.40% higher in comparison to that of the conventional ANN method. In addition, the newly proposed method also had better performance than seven previous methods that reported prediction accuracies in the range of 57.85–89.01%. The improvement of the HF risk prediction in the current study might be due to both the various contributions of the HF attributes and the proposed hybrid method. These findings suggest that the proposed method could be used to accurately predict HF risks in the clinic. © 2016 Elsevier Ltd

Expert Systems with Applications

An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction

The offshore/onsite teams’ knowledge transfer (KT) effectiveness is one of the key determinants for achieving the outcome of global software development (GSD) projects. In this study, the significance of offshore/onsite teams (GSD teams) KT effectiveness in GSD projects is measured through various factors: knowledge, team, technology, and organization factors. Moreover, the assessment framework for the integration of knowledge, team, technology, and organization factors for evaluating KT effectiveness in GSD projects has not been adequately available in the existing literature. For this motivation, the main objective of this study is to propose the assessment framework to evaluate offshore/onsite teams KT effectiveness with reference to GSD project outcome. For evaluating KT effectiveness of GSD teams, we have integrated three Fuzzy Multi-Criteria Decision Making (FMCDM) methodologies: (a) Fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), (b) Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and (c) Elimination Et Choix Traduisant la REaite (ELECTRE). Further, the hybridization of fuzzy DEMATEL, TOPSIS, and ELECTRE has not available in the existing literature. Based on this research gap, we have integrated fuzzy DEMATEL, TOPSIS, and ELECTRE approach for evaluating KT effectiveness of offshore/onsite teams in the context of GSD project outcome. Subsequently, the applicability and capability of proposed framework has been validated by software experts at Inowits Software Organization in India.

Journal	Data powered by TypesetApplied Soft Computing
Publisher	Data powered by TypesetElsevier BV
ISSN	1568-4946
Open Access	0