Teaching-Learning-based optimization (TLBO) is a recently proposed population based algorithm, which simulates the teaching-learning process of the class room. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. In this paper, the effect of elitism on the performance of the TLBO algorithm is investigated while solving unconstrained benchmark problems. The effects of common control parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 76 unconstrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. A statistical test is also performed to investigate the results obtained using different algorithms. The results have proved the effectiveness of the proposed elitist TLBO algorithm.

Cash flow ratios help financial users get relevant information about financial resources for a given time. Cash flow ratios are now used more than the traditional ones because it is more effective and justified. Cash flow based ratios are especially surprising because they do not only play a significant role in the credit rating of evaluation, but also forecast the failure of a corporation. In this study, we perform an empirical investigation on a company named CMC. From the study, it is clear that the liquidity and solvency positions of the company were moderate whereas the company maintained low profitability. On the other hand, the efficiency and sufficiency ratios of the study give us a new look on financial judgement.

In precision manufacturing, especially in making of holes on the parts during drilling process for precision assembling of parts facing problems with burr formation. Drilling is one of the finishing operations in the production cycle, removal of burrs during drilling process is a time consuming and non-value added process to the manufacturing sector. In this paper, we developed an analytical models for thrust force, torque and burr size with variable clearance angle of drill bit geometry especially for Aluminium alloys used for automotive applications. An analytical model results were obtained by writing a code in MATLAB @ 2010 software for aluminium alloy series such as Al 6061, Al 2014 and Al 7075. In an economic front, de-veloped mathematical models are benefitted to reduce experimentation, these results reveal that at the beginning of the drilled hole due to indentation of chisel edge, more thrust and torque was identified, beyond that suddenly thrust force was lowered, cutting forces by the lip edges were increased from beginning of the process to progress of drilling process. The proposed model approach is helpful to the budding entrepreneurs in the related areas to select optimal combination of drilling parameters to attain multiple performance characteristics of responses especially in burr size to prevent the post finishing operations up to certain extent.

The designers often face the problem of choosing the best fitted material for a specific application from a huge array of available alternatives while simultaneously fulfilling all the given design requirements. For dealing with the material selection problems, a systematic and efficient approach is thus necessary. Selection of an optimal material from among various alternatives based on different conflicting subjective as well as objective attributes can be defined as a typical multi-criteria decision-making (MCDM) problem. The material selection problems for diverse engineering applications have already been solved by the past researchers employing different MCDM approaches. In this paper, the feasibility of Q-analysis technique as an MCDM tool is explored for arriving at the most appropriate decision regarding materials selection. Its applicability is demonstrated with the help of four illustrative examples and its capability to provide almost accurate material selection decisions is also validated.

The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA). Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.

This research paper examines the role of cloud computing in promoting sustainable development. Cloud Computing (CC) has emerged as a transformative technology that has the potential to reduce the environmental impact of businesses and organizations, while also enabling economic growth and social development. The paper explores the environmental benefits of cloud computing, including energy efficiency, reduced carbon emissions, and the potential for renewable energy integration. It also examines the economic and social benefits of cloud computing, including cost savings, increased productivity, and improved access to technology. The paper concludes by highlighting the potential challenges and opportunities associated with the adoption of cloud computing for sustainable development and identifies key areas for future research and policy action. Overall, the paper argues that cloud computing has the potential to play a critical role in promoting sustainable development, and that further research and policy action are needed to realize its full potential.

Due to the emergent government regulations and stronger public awareness about environment today organizations simply cannot discard environmental concern if these companies want to stay alive in the international market. Environmental management is becoming more and more important for companies for sustainable development. If the industries of developing countries have to export to developed nations they have to match up with developed countries’ environmental standards. The emphasis on the environmental protection is not only due to organizational stakeholders but also governments, customers, employees, competitors and communities. Environmental issues in manufacturing sectors are not investigated appropriately in developing countries. The objectives of this paper are to review the literature on drivers and barriers for the implementation of Green Supply Chain Management (GSCM). After providing a background on GSCM, categories and review the literature on various issues/ factors for the recent GSCM, the concluding remarks for this review is also presented.

The present study focused on the Taguchi experimental design technique of Friction Stir Welds of dissimilar aluminum alloys (AA2024-T6 and AA6351-T6) for tensile properties. Effect of process parameters, rotational speed, Traverse speed and axial force, on tensile strength was evaluated. Optimized welding conditions for maximize tensile strength were estimated in order to improve the productivity, weld quality. Non-linear regression mathematical model was developed to correlate the process parameters to tensile strength. The results were verified by conducting the confirmation tests at identified optimum conditions.

Maintenance Quality Function Deployment (MQFD) is a model, which enhances the synergic power of Quality Function Deployment (QFD) and Total Productive Maintenance (TPM). One of the crucial and important steps during the implementation of MQFD is the determination of the importance or weightages of the critical factors (CF) and sub factors (SF). The CFs and SFs have to be compared precisely for the successful implementation of MQFD. The crisp pair-wise comparison in the conventional Analytical Hierarchy Process (AHP) may be insufficient to determine the degree of weightage of CFs and SFs where vagueness and uncetainties are associated. In this paper, a modification of AHP based MQFD by incorporating fuzzy operations is proposed, which can improve the accuracy of determination of the weightages. A case study showing the applicability of this method is illustrated in this paper.