ABSTRACT This paper proposes a new Multi-Objective Equilibrium Optimizer (MOEO) to handle complex optimization problems, including real-world engineering design problems. The (EO) is recently reported physics-based metaheuristic algorithm, and it has been inspired by the models used predict equilibrium state dynamic state. A similar procedure utilized in MOEO combining different target search s...

The enhancement of photovoltaic (PV) energy systems relies on an accurate PV model. Researchers have made significant efforts to extract parameters due their nonlinear characteristics the system, and lake information from manufactures’ system datasheet. estimation using optimization algorithms is a challenging problem in which wide range research has been conducted. idea behind this challenge s...

The knapsack problem is one of the most widely researched NP-complete combinatorial optimization problems and has numerous practical applications. This paper proposes a quantum-inspired differential evolution algorithm with grey wolf optimizer (QDGWO) to enhance diversity convergence performance improve in high-dimensional cases for 0-1 problems. proposed adopts quantum computing principles suc...

This paper gives and analyses data-driven prediction models for the energy usage of appliances. Data utilized include readings temperature humidity sensors from a wireless network. The building envelope is meant to minimize demand or required power house independent appliance mechanical system efficiency. Approximating mapping function between input variables continuous output variable work reg...