Green metaverse is the world that embraces the evolution, therefore, it ought to be in line with the climate goals. However, with the coming of contradiction, governance and policy play a huge role in the path of environmental sustainability and digital transformation to usher a smarter and greener future. For this purpose, we propose a simulation framework based on fuzzy logic and genetic algorithms to evaluate and optimize the digital ecosystem concerning technological and environmental innovation, social and economic sustainability. It involves a fuzzy control system with twenty-nine input variables, including essential environmental indicators such as carbon footprint, energy consumption, water usage, waste generation, pollution levels, and biodiversity effect. Strategic metrics include various factors such as green investments, circular economy practices, smart infrastructure, operational efficiency, and community engagement. Additionally, aspects such as waste management, pollution control, climate resilience, ecojustice, fair trade, and recognition of indigenous knowledge are required to understand the complex interrelationships of sustainability. Dynamically, each variable is accompanied by Gaussian or triangular membership functions representing low, medium, and high levels. Four fuzzy rules are applied targeting environmental and ecological impact; investments and innovations grounded in sustainability; social community engagement, regulation, and compliance; and resource dependency and risk management, from which the output variable is obtained for the green metaverse. This output is then subject to optimization by a genetic algorithm to reach an optimal solution producing a score for the green metaverse of about 82.95% with a moderate carbon footprint, with high green investment, and balanced resource and risk management strategies. The framework enhances the capability of managing sustainability interrelations through an evidential approach with minimal adverse impact. It has the potential as a scalable platform to explore scenarios for policy development, striving for greater applicability in both academic research and real-world governance.