Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp. Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp. This report has been prepared in the framework of “Energy Connectivity in Central Asia” project financed by GIZ on behalf of the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection. The co-authors of this report are: Ms. Nadejda. A report co-authored by an SEI expert, using SEI's flagship energy modelling tools, finds that improved energy connectivity in Central Asia can save the region at least USD 1. This review paper focuses on balancing economic, environmental, social. Five countries of Central Asia - Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan - face significant environmental challenges, including high levels of pollution and impacts of climate change. 4 billion USD of annual savings in electricity production between now and 2050 (at moderate CO2 prices - $26/t CO2 in 2030, $65/t CO2 in 2050 - harmonized across all countries to avoid carbon leakage).
