Journal of Computational and Cognitive Engineering

Efficiently Generating Bounded Solutions for Very Large Multiple Knapsack Assignment Problems

2023-06-08T13:40:24+08:00

The Multiple Knapsack Assignment Problem (MKAP) is an interesting generalization of the Multiple Knapsack Problem which has logistical applications in transportation and shipping. In addition to trying to insert items into knapsacks in order to maximize the profit of the items in the knapsacks, the MKAP partitions the items into classes and only items from the same class can be inserted into a knapsack. In the literature, the Gurobi integer programming software has solved MKAPs with up to 1240 variables and 120 constraints in at most 20 minutes on a standard PC. In this article, using a standard PC and iteratively loosening the acceptable tolerance gap for 180 MKAPs with up to 20,100 variables and 1,120 constraints, we show that Gurobi can, on average, generate solutions that are guaranteed to be at most 0.17% from the optimums in 43 seconds. However, for very large MKAPs (over a million variables), Gurobi’s performance can be significantly improved when an initial feasible solution is provided. Specifically, using from the literature, a heuristic and 42 MKAP instances with over 6 million variables and nearly 90,000 constraints, Gurobi generated solutions guaranteed to be, on average, within 0.21% of the optimums in 10 minutes. This is a 99% reduction in the final solution bound (gap between the best Gurobi solution and the best upper bound) compared to the approach without initial solution inputs. Hence, a major objective of this article is to demonstrate for what size MKAP instances providing Gurobi with an initial heuristic solution significantly improves performance in terms of both execution time and solution quality.

Received: 3 April 2023 | Revised: 8 June 2023 | Accepted: 12 June 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Revisiting Shift Cipher Technique for Amplified Data Security

2022-07-18T11:02:04+08:00

Ever since manual work is overtaken by technology and the rapid advancement in the technologies for performing all kinds of work online has created new possibilities for the organizations and institutions of all types. But this has also created opportunities for attackers and opponents by reducing the powers of existing controls over data sharing. All private, public and any other sectors are using the internet for sharing their data. Transmission of unencrypted data over the internet is not secure as it poses many privacy concerns as they can be easily hacked and misused by any unintended person. So, everyone is concerned about safe and secure ways of data transmission in order to avoid leak of private data, as hackers always try to chase the transmitted data and to recover it and therefore various different techniques are developed in order to make data transmission more secure. Encryption is essential to protect and prevent such lapses in the transmission of sensitive information over the internet and any other networks. In this paper, the author has worked on a better version of Caesar cipher and invented a method in which modular arithmetic is used to convert plaintext into ciphertext in order to amplify and to bolster up the security of the sensitive data or information, the author composed the decryption method in such a way that it is no way related to encryption by involving the divisibility tests and arithmetic modulo.

Received: 29 May 2022 | Revised: 18 July 2022 | Accepted: 16 August 2022

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Investigating and Classifying the Level of Thermal Runaway-Induced Failure Energy Storage Systems in Photovoltaics

2023-11-14T11:25:50+08:00

In a photovoltaic system, the electricity generated by a solar panel can depend on the amount of sunlight available at any given time. Due to the nonlinear behavior of this energy, the storage component of the system is critical. As a result, many solar panel systems are equipped with batteries. However, changes in environmental and other conditions can cause damage to these batteries. This study explores novel technologies for detecting thermal runaway failures in lithium-ion batteries. Specifically, the study employs image processing techniques to detect structural failures and applies deep learning techniques for automatic classification. Thermal damage to a battery can result in irreparable harm, making design and construction considerations crucial. Through image analysis, any internal changes in the battery can be transformed into a measurable variable, providing a reliable indication of potential failure. The study compares the current series with previous ones to highlight the structural differences. Results confirm that the proposed approach has significant potential for detecting and estimating internal variations during production. Overall, the proposed method can serve as a valuable tool for drafting and implementing a comprehensive plan to address early problems in the battery.

Received: 8 September 2023 | Revised: 14 November 2023 | Accepted: 21 November 2023

Conflicts of Interest

The author declares that she has no conflicts of interest to this work.

Data Availability Statement

The data that support the findings of this study are openly available in National Renewable Energy Laboratory (NREL) at https://www.nrel.gov/transportation/battery-failure.html.

Refined Fuzzy Soft Sets: Properties, Set-Theoretic Operations and Axiomatic Results

2023-05-25T17:23:41+08:00

This article discusses the results of an investigation into refined fuzzy soft sets, a novel variant of traditional fuzzy sets. Refined fuzzy soft sets provide a versatile method of data analysis, inspired by the need to deal with uncertainty and ambiguity in real-world data. This research expands on prior work in fuzzy set theory by investigating the nature and characteristics of refined fuzzy soft sets. They are useful in decision-making, pattern recognition, image processing, and control theory because of their capacity to deal with uncertainty, ambiguity, and the inclusion of expert information. This study analyzes these fuzzy set models and compares them to others in the field to reveal their advantages and disadvantages. The practical uses of enhanced fuzzy soft sets are also examined, along with possible future research strategies on this exciting new topic.

Received: 14 March 2023 | Revised: 25 May 2023 | Accepted: 14 June 2023

Conflicts of Interest

Harish Garg is the editor-in-chief for Journal of Computational and Cognitive Engineering, and was not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Cognitive Computing Smart System: How to Remove Ambiguities

2022-11-16T14:50:45+08:00

The purpose of this paper is to accurately distinguish a series of ambiguities commonly encountered in human-computer interaction
through smart system studied and cognitive computing methods, and then make reasonable predictions and responses. The method is as follows: first, make a basic classification of the various ambiguities encountered by cognitive computing and smart systems, then make a corresponding match for each type of ambiguity, and then apply the theory of smart system engineering to guide the translation or interpretation. The characteristic is that the process of prediction and decision-making is the integration of formal methods based on rules and statistics. The result is the discovery of an efficient way to resolve various ambiguities in a trinity of the natural language understanding, expert knowledge expression, and software pattern recognition. Its significance lies in the acceleration of the formation of the disruptive innovation system of the core basic invention of the new general information technology and its supporting software and hardware technologies, and the popularization of the Z standard of cultural gene system engineering practice. In the author’s opinion, the first meaning is to regard mind as an attribute of brain, and the second meaning is to further regard language, knowledge, and software as attributes of mind.

Received: 26 September 2022 | Revised: 11 November 2022 | Accepted: 16 November 2022

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

COVID-19 Outbreak with Fuzzy Uncertainties: A Mathematical Perspective

2022-07-04T14:06:20+08:00

In this article, we design a mathematical SEQAIMR (susceptible, exposed, quarantined, asymptomatic, symptomatic, isolated, recovered) epidemic model and investigate the nature of the system. We transform the crisp model into the fuzzy model. All the biological parameters are treated as triangular fuzzy numbers (TFNs). With the help of utility function method, the fuzzy model is defuzzified. We use the MATLAB codes to solve the system of equations and to predict different situations under different values of the control parameters. Lastly, optimal control for COVID-19 disease is explained.

Received: 30 April 2022 | Revised: 4 July 2022 | Accepted: 13 July 2022

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Strategy Generation for Risk Minimization of Renewable Energy Technology Investments in Hospitals with SF TOP-DEMATEL Methodology

2023-06-12T10:45:21+08:00

Effective risk management plays an important role to improve renewable energy technology investments. Because of this issue, necessary actions must be implemented to effectively manage these risks. However, having high costs is the biggest disadvantage of the implementation of these actions. Therefore, it is not financially possible to implement different strategies together. In other words, it is necessary to identify the most important of these strategies. Accordingly, the purpose of this study is to make a priority evaluation for the risk strategies related to renewable energy technologies in hospitals. For this purpose, a new model is generated with spherical fuzzy (SF) TOP-DEMATEL technique. In this process, significant indicators are defined based on literature evaluations. In the next process, the weights of these indicators are calculated. The main contribution of this study is that a new technique is proposed by the name of TOP-DEMATEL. In this scope, the final steps of TOPSIS are integrated to the analysis process of DEMATEL to overcome criticisms for classical DEMATEL technique. Moreover, a priority evaluation is carried out to understand the most critical risk management strategies in renewable energy technology investments. With the help of this analysis, it can be much easier to take risk management actions without having financial difficulties. It is determined that the weighting results of the criteria are quite similar for different t values. This situation identifies that the proposed model provides coherent and reliable results. It is concluded that government support is the most important strategy in this context. Additionally, technological improvements also play a crucial role for this situation. It is strongly recommended that governments should establish appropriate legal and regulatory frameworks to promote renewable energy projects. These frameworks can facilitate the financing and licensing of projects and offer economic incentives such as tax incentives and subsidies.

Received: 31 May 2023 | Revised: 22 June 2023 | Accepted: 9 July 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Data Fusion Technique for E-Learning Evaluation Based on Evidence Theory

2022-10-06T11:23:50+08:00

To reduce the risk of viral infection during the coronavirus pandemic, all academic institutions have turned to online learning in recent years. The evolution of online classes presents new obstacles for academic specialists, particularly in underdeveloped nations where participants have limited access to technological gadgets. Even while some elements of online and traditional on-campus learning are comparable, online learning requires more factors to analyze, such as student evaluation. Because of the various surroundings that participants are exposed to during online education, the topic of electronic learning environments must be discussed. It calls for the development of new methodologies and procedures for assessing participants’ knowledge and skill development. Based on evidentiary theory and the data fusion idea, this research provides a new technique to evaluate participation. Because it is versatile in simulating the wide spectrum of uncertainty inherent in natural contexts, evidential theory is progressively spreading. The approach suggested is appropriate for dealing with all forms of online courses. Furthermore, it enables educators to improve academic performance by providing continuous participant feedback. After exposing participants’ weaknesses, the instructor can redirect learning processes. The experimental findings of three online university courses demonstrate the efficacy of this strategy.

Received: 15 August 2022 | Revised: 19 September 2022 | Accepted: 7 October 2022

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Cost Analysis of Solar Water Pumping System for Small Town Water Supply

2022-05-16T14:09:52+08:00

This study investigates the economics of a solar water pumping system for usage in small towns. The system consists of two solar panels, an inverter, a water pumping mechanism, and two parallel tanks. Using the transition diagram, a system of first order linear ordinary differential equations is generated and used to generate a statement of system availability and profit. To validate the expressions of system availability and profit, numerical experiments in the MATLAB software in the form of tables and graphs are utilized. According to the findings, the system's profitability increases as the value of repair rates across all subsystems increases, while it decreases when the value of failure rates across all subsystems increases.

Received: 10 April 2022 | Revised: 16 May 2022 | Accepted: 24 May 2022

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Bonferroni Mean Operators Based on Interval-Valued Picture Hesitant Fuzzy Information and Their Application in Decision-Making Problems

2023-05-15T10:28:55+08:00

In this article, we invent the Bonferroni mean (BM) operators using interval-valued picture hesitant fuzzy (IVPHF) technique, called IVPHF Bonferroni mean (IVPHFBM), IVPHF-weighted BM (IVPHFWBM), IVPHF geometric BM (IVPHFGBM), and IVPHF-weighted geometric BM (IVPHFWGBM) operators. These presented techniques are very beneficial and valuable because these are modified versions of many existing techniques. Moreover, we also examine three basic properties of each presented operator. In addition, we demonstrate the technique of multi-attribute decision-making (MADM) problem and try to describe it with the presence of evaluated techniques to show the capability and superiority of the invented theory. In last, we compare the prevailing techniques with presented studies to illustrate the supremacy and effectiveness of the derived approaches.

Received: 10 April 2023 | Revised: 15 May 2023 | Accepted: 25 May 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.