This study compares the performance of the optimal installation of solar-assisted combined
cooling, heating, and power system (CCHP) running different strategies using the energy …

This work extends a near feasibility threshold (NFT) based adaptive penalty function for
constrained multiobjective optimization. The NFT zone adjoining the feasible region is …

Multi-objective optimization algorithms have shown effectiveness on problems with two or
three objectives. As the number of objectives increases, the proportion of non-dominated …

Constrained multi-objective optimization problems (CMOPs) require a delicate balance
between satisfying constraints and optimizing objectives. Existing constrained multi …

This paper proposes an evolutionary algorithm with hierarchical clustering based selection
for multi-objective optimization. In the proposed algorithm, a hierarchical clustering is …

Water quality prediction is an indispensable task in water environment and source
management. The existing predictive models are mainly designed by data-driven artificial …

Measurement errors, spatial incompleteness, and parameter uncertainties frequently lead to
significant deviations between the estimated correction coefficients of structural model …

Energy-awareness in the industrial sectors has become a global consensus in recent
decades. Green scheduling is acknowledged as an effective weapon to reduce energy …

The multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes
a multiobjective optimization problem (MOP) into several scalar subproblems and then …

Control systems are used in safety-critical applications where tuning the system parameters
is required to ensure safe and secure operation. The process of tuning these parameters …