In today’s world, the demand for sustainable third-party reverse logistics providers (S3PRLPs) becomes an increasingly considerable issue for industries seeking improved customer service, cost reduction and sustainability perspectives. However, the assessment and selection of right S3PRLP is a complex uncertain decision-making problem due to involvement of numerous conflicting attributes, imprecise human mind and lack of information. Recently, Fermatean fuzzy set (FFS) has been recognized as one of the suitable tools to tackle the uncertain and inaccurate information. In this paper, we introduce a hybrid methodology based on CRITIC and EDAS methods with Fermatean fuzzy sets (FFSs) to solve the S3PRLP selection problem in which the attributes and decision makers’ weights are completely unknown. In this framework, CRITIC approach is applied to calculate the attribute weight and EDAS method is used to evaluate the priority order of S3PRLP options. To do this, a new improved generalized score function (IGSF) is developed with its elegant properties. Also, a formula is discussed to calculate the decision makers’ weights based on the developed IGSF. Next, developed framework is applied to assess a case study of S3PRLP selection problem with Fermatean fuzzy information, which elucidates the usefulness and practicality of the proposed method. Finally, comparative study is implemented to show the strength of introduced framework with extant approaches. The outcomes of the work confirm that the introduced approach is more feasible and well-consistent with the other extant approaches.

Bioenergy is a kind of renewable energy that can potentially contribute to a broad spectrum of economic, environmental, and societal objectives and aid sustainable development. The assessment, management, and monitoring of the diverse bioenergy production technology alternatives are complex in nature and deliver different benefits due to the lack of precise and comprehensive data. Selection of an optimal bioenergy production technology (BPT) alternative is considered a complex multi-criteria decision-making (MCDM) problem that involves many incompatible tangible and intangible as well as qualitative and quantitative criteria. The procedure of defining and evaluating the weights of the criteria is an important concern for decision experts because the assessment and the final selection of the BPT alternative are carried out on the basis of the defined set of criteria. Intuitionistic fuzzy sets (IFSs) have received considerable attention due to their ability to handle the imprecision and vagueness that can arise in real-life situations. Thus, this study presents an integrated approach, based on stepwise weight assessment ratio analysis (SWARA) and complex proportional assessment (COPRAS) approaches, for the selection of BPT alternatives. In the integrated framework, criteria weights are determined by the SWARA procedure, and the ranking of BPT alternatives is decided by the COPRAS method using IFSs. The criteria weights evaluated by this approach involve the imprecision of experts’ opinions, which makes them more comprehensible. To express the efficiency and applicability of the integrated framework, a BPT selection problem is presented using IFSs. In addition, this study involved sensitivity analysis with respect to various sets of criteria weights to reveal the strength of the developed approach. The sensitivity analysis outcomes indicate that the agricultural and municipal waste of biogas (S3) consistently secures the highest rank, despite how the criteria weights vary. Finally, a comparative study is discussed to analyze the validity of the obtained result. The findings of this study confirm that the proposed framework is more useful than and consistent with previously developed methods using the IFSs environment.

This study proposes a systematic methodology of the adoption of Internet of Things (IoT) barriers (IoTBs) that exist in the waste management structures of smart cities (SCs) in growing economies likely India. A hybrid multi-attribute decision-making (MADM) is applied and has recognized 15 IoTBs from literature and experts opinions obstructing the IoT adoption in SCs of India. The different IoTBs are studied using the similarity measure-based new weighting approach, and the combined compromise solution (CoCoSo) method. Considering that Fermatean fuzzy sets (FFSs) can represent this uncertainty, this paper proposes a decision-making framework for waste management system solutions based on the FFSs and builds a complete evaluation index system. Herein, we first combine the Archimedean Copula operations and Archimedean operations and term them as 'generalized Archimedean Copula operations' for FFSs. Based on these new operations, we develop the Fermatean fuzzy generalized Archimedean copula weighted averaging (FFGACWA) and Fermatean fuzzy generalized Archimedean copula weighted geometric (FFGACWG) operators. Then, we construct a decision algorithm based on FFWGAAC and FFWGGAC operators. Second, we propose new weighting procedure based on similarity measure to discuss the significance degree of IoTBs. Further, we apply this method to the evaluation and selection of a methodology of IoTBs in smart cities' waste management (SCWM) assignments, and prove the effectiveness of this method. The algorithm can represent the Fermatean fuzzy information in a complex environment. It cannot only consider the uncertainty of the decision-makers (DMEs) when giving the evaluation value but also synthesize the relationship between any numbers of evaluation criteria. Finally, the superiority of the methodology is discussed by sensitivity analysis and comparative study. The results show that the method can effectively handle the decision-making problems in complex environments. This paper will assist the representatives, stakeholders and government to know the importance of IoTBs affecting waste management processes, and it will certainly help them to take judgments for exterminating the IoTBs for an effective IoT employment in SCWM assignments.

To select a biomass crop type of the highest sustainability for the purpose of producing biofuel is recognized as a problem of the multi-criteria decision analysis (MCDA) type, as it comprises different conflicting criteria. To effectively address this problem, the present paper introduces a novel integrated approach using the complex proportional assessment (COPRAS) method under the intuitionistic fuzzy sets (IFSs). The proposed approach works based on the IFSs operators as well as an innovative process utilized in evaluating the attributes’ weights. To evaluate these weights, the subjective weights using the step-wise weight assessment ratio analysis (SWARA) model are integrated with the objective weights achieved using an entropy-based approach in order to attain more realistic weights. As MCDA problems inevitably suffer from different degrees of uncertainty, the proposed approach could be of great help to those who are required to make decisions in uncertain settings. The paper took into consideration a sustainable biomass crop selection problem to exemplify the effectiveness of the presented approach in handling real MCDA problems. Moreover, a sensitivity analysis with respect to the diverse values of the attributes is presented in order to assess the stability of the introduced model. This study reveals that the combination of the objective and subjective weights enhances the stability of the introduced approach with diverse attribute weights. Finally, the results of the introduced model are compared to some existing intuitionistic fuzzy information-based methods. The findings of the comparison confirm the efficiency of the present approach in performing the defined tasks under uncertain environments.

Due to quick advances in network and communication engineering, fast development of open source Internet network tools and technologies, per hour ratio of the exchange of privacy or confidentiality of the data in the form simple or complex files over the network, the Government's planning or any confidential amendment information, or any other important evidence of the agreement or deal If all these has been attacked or stolen by the malicious as a intention of tampering, will results catastrophic penalty for the society. So that the cost of securing such information is worthless as compared to the valuable information is the modern concept and current trends for research in the field of network protection technology [1]. Most of the IDS and IPS are based on two fundamental mechanisms; Misuse detection or signature based detection [2]. Signature based systems are simple to create and efficient to operate, but are only effective against known types of attack that has fixed pattern while Anomaly detection mechanisms, on the other hand, create a profile of typical behavior for a user and raise an alert when a user attempts an activity that does not fit his/her profile. This approach tends to be highly complete in that it can detect a previously unknown attack pattern, but it requires significant effort to develop algorithms that can create accurate user profiles. In this paper a behavioral based anomaly detector solution has been proposed based on the idea inferred from [2] and [4]. The novel thing about the proposed technique is the idea of MMO (Means, Motive and Opportunity) which speedup the detection rate and enhanced the capability of catching unknown attacks by applying anomaly on them. Proposed system has been applied on real-time traffic (flows) and obtained results found much more satisfactory. For sniffing real time traffic ourmon monitoring tool has been deployed on ubuntu 13.04.