Transformer, an attention-based encoder–decoder model, has already revolutionized the
field of natural language processing (NLP). Inspired by such significant achievements, some …

Power scheduling is an NP-hard optimization problem that demands a delicate equilibrium
between economic costs and environmental emissions. In response to the growing concern …

River flood routing computes changes in the shape of a flood wave over time as it travels
downstream along a river. Conventional flood routing models, especially hydrodynamic …

Life cycle optimization (LCO) refers to the integration of objectives calculated using a life-
cycle based framework into mathematical optimization problems. Application of LCO may …

Studies focusing on the optimization of waste-to-energy systems using metaheuristic particle
swarm optimization (PSO) are crucial in our pursuit of sustainable and renewable energy …

The multiobjective (MO) optimizers show great promise in solving constrained engineering
structural problems. This paper introduces a MO version of the Brown Bear Optimization …

Accurate parameter estimation of the equivalent circuit model (ECM) for Li-Ion batteries
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …

The principal aim of this article is to optimize the thermal and electrical efficiency of a
geothermal combined heat and power system through metaheuristic particle swarm …

The urgent demand for clean and renewable energy sources has led to the emergence of
the microgrid (MG) concept. MGs are small grids connecting various micro-sources, such as …

The increasing adoption of plug-in electric vehicles (PEVs) leads to negative impacts on
distribution network efficiency due to the extra load added to the system. To overcome this …