Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization.

The effective meta-heuristic technique known as the grey wolf optimizer (GWO) has shown its proficiency. However, due to its reliance on the alpha wolf for guiding the position updates of search agents, the risk of being trapped in a local optimal solution is notable. Furthermore, during stagnation, the convergence of other search wolves towards this alpha wolf results in a lack of diversity within the population. Hence, this research introduces an enhanced version of the GWO algorithm designed to tackle numerical optimization challenges. The enhanced GWO incorporates innovative approaches such as Chaotic Opposition Learning (COL), Mirror Reflection Strategy (MRS), and Worst Individual Disturbance (WID), and it's called CMWGWO. MRS, in particular, empowers certain wolves to extend their exploration range, thus enhancing the global search capability. By employing COL, diversification is intensified, leading to reduced solution stagnation, improved search precision, and an overall boost in accuracy. The integration of WID fosters more effective information exchange between the least and most successful wolves, facilitating a successful exit from local optima and significantly enhancing exploration potential. To validate the superiority of CMWGWO, a comprehensive evaluation is conducted. A wide array of 23 benchmark functions, spanning dimensions from 30 to 500, ten CEC19 functions, and three engineering problems are used for experimentation. The empirical findings vividly demonstrate that CMWGWO surpasses the original GWO in terms of convergence accuracy and robust optimization capabilities.

In the era of globalization, can renewable energy and eco-innovation be viable for environmental sustainability in BRICS economies?

Although energy is a necessary component of production and hence a contaminant, the environmental effect varies depending on the type of energy used. Renewable sources of energy can provide ecological advantages, particularly when contrasted with fossil fuels, which emit high levels of CO2 emissions. Thus, the research explores the impact of eco-innovation (ECO), green energy (REC), and globalization (GLOB) on the ecological footprint (ECF) in the BRICS nations using the panel nonlinear autoregressive distributed lag (PNARDL) technique between 1990 and 2018. The empirical results indicate that there is cointegration in the model. The results from the PNARDL show that a positive shift in renewable energy, eco-innovation, and globalization decreases the ecological footprint, while positive (negative) shifts in non-renewable energy and economic growth intensify the ecological footprint. The paper suggests several policy recommendations based on these results.

Environmental sustainability in Vietnam: evaluating the criticality of economic globalisation, renewable energy, and natural resources.

Vietnam's goal of achieving a certain level of decarbonisation by 2030 is difficult despite its awareness of the threat posed by climate change. However, the country is endowed with natural resources and the increasing dependence on the global economy coupled with greater investment in alternative energy sources are some of the factors responsible for economic expansion in recent years. Hence, the question arises "what are the environmental impacts of economic globalisation, economic growth, natural resources, and renewable energy in Vietnam?", which constitutes a major policy problem. In this study, a time series dataset stretching from 1984 to 2019 is employed to scrutinise the impact of economic globalisation, economic growth, natural resources, and renewable energy on Vietnam's CO2 emissions. This goal is achieved by employing the ARDL bounds testing procedure, dynamic ARDL, and spectral Granger-causality test. Moreover, the outcomes from the dynamic ARDL showed that economic globalisation and economic growth lead to environmental deterioration, whereas it is mitigated by renewable energy. Lastly, the outcomes from the spectral Granger-causality test indicate that a feedback causality association exists between CO2 emissions and the regressors, namely economic globalisation, renewable energy, and economic growth, while no causality connection exists between CO2 emissions and natural resources. Hence, we suggest that actions for reducing emissions should involve the implementation of energy-efficient techniques and renewable technologies within the energy value chain.

Toward a sustainable environment and economic growth in BRICS economies: do innovation and globalization matter?

Over the last few decades, environmental deterioration has accelerated significantly. Environmental degradation has been a subject of research across the world because of its impact on billions of people. However, there has been no international agreement on lowering the utilization of energy and CO2 emissions (CO2), while demand for fossil fuels grows in emerging economies. On the other hand, the recent COP26 summit brought all parties together to accelerate action toward reaching the goals of the Paris Agreement and the UN Framework Convention on Climate Change. Although previous research shows that international trade promotes positive socioeconomic outcomes, other experts argue that it contributes to natural resource shortages and ecological deterioration. Thus, the current research considers the effect of international trade, renewable energy use and technological innovation on consumption-based carbon emissions (CCO2), coupled with the role of financial development and economic growth in the BRICS economies between 1990 and 2018. Moreover, this research utilizes the common correlated effects mean group (CCEMG), augmented mean group (AMG) and Dumitrescu and Hurlin (2012) causality methods to assess these interrelationships. The study findings reveal that renewable energy use, exports and technological innovation mitigate CCO2, whereas economic growth and imports trigger CCO2 in the BRICS economies. The panel causality outcomes also reveal that all the variables except financial development can predict CCO2 emissions. Based on the study findings, we recommend the adoption of policies, regulations and the development of legislative frameworks that promote technological innovation and the shift toward sustainable energy.