The study suggests a better multi-objective optimization method called 2-Archive Multi-
Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss …

Transforming a constrained optimization problem (COP) into a multi/many-objective
optimization problem (MOP/MaOP) represents a practical approach for solving COPs. This …

Reentry trajectory optimization for reusable launch vehicles (RLVs) is a class of optimal
control problems with multiple highly nonlinear constraints. Nature-inspired algorithms …

Multi-objective and multi-stage decision-making problems require balancing multiple
objectives at each stage and making optimal decision in multi-dimensional control variables …

Solving large-scale, constrained, and non-linear optimization problems is crucial for the
Internet of Things (IoT) due to its wide range of real-life applications. However, there is no …

In practical engineering problems, uncertainties due to prediction errors and fluctuations in
equipment efficiency often lead to constrained many‐objective optimization problem with …

Many real-world optimization problems are inherently constrained, presenting significant
challenges to the application of evolutionary algorithms. Successfully managing these …

Recently, gradient-based repair methods have been commonly introduced into constraint-
handling techniques to handle linear and non-linear constraints. These gradient-based …

Constrained multi-objective problems are difficult for researchers to solve because they
contain infeasible regions. To address this issue, this paper proposes two cooperative …

This paper focuses on the implementation of Nature inspired metaheuristic algorithms in
Wireless Sensor Networks (WSNs) such as Particle Swarm Optimization (PSO), Whale …