A Sensitivity Analysis on Weight Sum Method MCDM Approach for Product Recommendation

Kumar, Gaurav; Parimala, N.

doi:10.1007/978-3-030-05366-6_15

Cited by 9 publications

(5 citation statements)

References 5 publications

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“…Weighted Sum Method: An effective decision-making framework known as MCDM (Multi-Criteria Decision Making) is employed to evaluate and rank various options in the presence of multiple, often conflicting, selection criteria. MCDM methodologies provide a structured and systematic approach to addressing challenges, facilitating a clear and organized way for decision-makers to assess the problem and tailor it to align with their specific requirements [15]. In scenarios involving Multi-Criteria Decision Making (MCDM), the determination of the sequence of options is greatly contingent on the scrutiny of data, encompassing the significance and nature of attributes within both the application and choice matrices.…”

Section: Methodsmentioning

confidence: 99%

Enabling Efficient IoT Device Connectivity and Dynamic Network Management through SDN: A Weighted Sum Method Approach

2023

Data Analytics and Artificial Intelligence

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SDN-Enabled IoT Networks bring about a transformative shift in conventional network models by integrating the core principles of Software-Defined Networking (SDN) into the realm of the Internet of Things (IoT). This integration empowers the agile and effective management of IoT devices, facilitating smooth connectivity, optimized distribution of resources, and flexible network setups. Through the consolidation of control and the utilization of virtualization methods, SDN-Enabled IoT Networks amplify scalability, security, and real-time responsiveness. This addresses the obstacles presented by the extensive proliferation of IoT devices. This paradigm transition heralds a fresh era of interconnectedness, where SDN assumes a central role in harmonizing the intricate interplay of IoT devices and services. The rapid expansion of Internet of Things (IoT) devices has introduced unparalleled complexities in overseeing networks and establishing connections. This compels the need for inventive strategies to effectively manage the substantial surge of IoT devices and their ever-changing connectivity prerequisites. Software-Defined Networking (SDN) emerges as a promising approach to tackle these issues by enabling the flexible management of networks and allocation of resources. This study investigates the amalgamation of SDN within the realm of IoT, aiming to streamline device connections, optimize data transmission efficiency, and accommodate adaptable network setups. Introducing an innovative weighted sum technique for resource allocation optimization, this work lays the foundation for a comprehensive framework that bolsters IoT network performance and expandability. Four different SDN implementations are examined, including the Conventional IoT Network, SDN-enabled IoT utilizing Centralized Control, SDN-enabled IoT employing Distributed Control, SDN-enabled IoT with Hierarchical Control, and SDN-enabled IoT utilizing Hybrid Control. The assessment considers various aspects such as Enhanced Scalability, Enhanced Traffic Engineering, Heightened Security, Implementation Complexity, Difficulty of Migration, and Reliance on Vendors. The Conventional IoT Network secures a moderate 3rd position with a Preference Score of 0.56030, while the SDN-enabled IoT with Centralized Control holds the 5th rank at 0.49732, despite excelling in specific domains. The SDN-enabled IoT with Distributed Control achieves the top rank with a notable Preference Score of 0.79414 due to comprehensive performance, followed by the SDN-enabled IoT with Hierarchical Control securing the 2nd spot (Preference Score: 0.57022), and the SDN-enabled IoT with Hybrid Control taking the 4th position (Preference Score: 0.51300), particularly excelling in Traffic Engineering.

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Section: Methodsmentioning

confidence: 99%

Enabling Efficient IoT Device Connectivity and Dynamic Network Management through SDN: A Weighted Sum Method Approach

2023

Data Analytics and Artificial Intelligence

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“…The criteria weights are part of the MCDM methods and affect the evaluation process (Zavadskas and Podvezko, 2016). As can be seen from the studies carried out, the importance of the criteria has a strong effect on the MCDM results (Zavadskas and Podvezko, 2016;Alemi-Ardakani et al 2016;Kumar and Parimala, 2019). Table 10 shows the criteria weights for all dimensions and years.…”

Section: Application Of Copeland Methods For Integrated Evaluation Ap...mentioning

confidence: 99%

Comparative Analysis of MCDM Methods for the Assessment of Corporate Sustainability Performance in Energy Sector

Ersoy

Taslak

2022

eab

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Energy is an important input for production, growth, and development. A sustainable energy sector, where energy production and consumption balance is ensured, constitutes a key point for nature and humanity. In this study, a multidimensional framework is presented to measure corporate sustainability in the energy sector. Based on this framework, the sustainability performance of energy companies operating in the Asia and Europe regions is measured by hybrid multiple-criteria decision-making (MCDM) methods, taking into account the economic, environmental, and social dimensions of sustainability. The Entropy method is used to determine the weights of the criteria, the Proximity Indexed Value (PIV) - Range of Value (ROV) - Grey relational analysis (GRA) - Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) methods are used to rank the alternatives. The Copeland method is used to obtain a single rational ranking from different rankings. Based on the obtained results, it is concluded that energy companies in the Asian region are more sustainable than in the European region. Moreover, Thailand is the most sustainable country in the Asian region. The proposed framework can be contribute to the development of the energy sector.

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“…The first is called the synthesis criterion approach; it consists in transforming the multi-criteria problem into a simple mono-criterion problem. As an example of methods coming under this approach: we cite the Weight Sum Method (WSM) [7], the Goal Programming method [8], the Technique for Order of Preference by Similarity to the ideal solution (TOPSIS) [9], and many other methods. The second approach is known as the outranking approach, where we build a comparison relationship between actions, called the outranking relationship.…”

Section: Analysis Methods and Comparison Between Mcdm Methodsmentioning

confidence: 99%

New Metrics to Measure the Quality of the Ranking Results Obtained by the Multi-criteria Decision-Making Methods

Abounaima

Lamrini

Mazouri

et al. 2021

Lecture Notes in Electrical Engineering

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Nowadays, there is a panoply of multi-criteria decision-making methods which are proposed in the literature to solve the ranking problematic, where each method has its resolution process and has its drawbacks and advantages. These methods aim to rank from best to worst a finite set of alternatives while taking into account a set of conflictual criteria. The purpose of this article is to propose specific metrics that will be useful to measure the quality of the rankings obtained by different methods. Thus, these quality measures can help the decision-maker to choose the best ranking objectively when adopting several methods. To show and prove the importance and relevance of the metrics proposed, a set of twenty-five examples of rankings will be examined. The results of the experiment conclusively show that all the proposed metrics lead to significant and equivalent quality measures.

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A Sensitivity Analysis on Weight Sum Method MCDM Approach for Product Recommendation

Cited by 9 publications

References 5 publications

Enabling Efficient IoT Device Connectivity and Dynamic Network Management through SDN: A Weighted Sum Method Approach

Enabling Efficient IoT Device Connectivity and Dynamic Network Management through SDN: A Weighted Sum Method Approach

Comparative Analysis of MCDM Methods for the Assessment of Corporate Sustainability Performance in Energy Sector

New Metrics to Measure the Quality of the Ranking Results Obtained by the Multi-criteria Decision-Making Methods

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