Search Biases in Constrained Evolutionary Optimization

Evolutionary pattern search algorithms for unconstrained and linearly constrained optimization

Redescribe aconvergence theory forevolutionary pattern search algorithms (EPS.4S) ona broad class of unconstrained and linearlyconstrainedproblems. EPSAS adaptively modify the step size of the mutation operator in response to the success of previous optimization steps. The design of EPSAS is inspired by recent analysesof pattern search methods. Our analysis significantly extends the previous co...

Constrained Optimization Evolutionary Algorithm

Constrained optimization evolutionary algorithm (COEA) is a mathematical programming problem frequently encountered in the field of engineering application. Solving constrained optimization problems by COEA has become an important research area of evolutionary computation in recent years. In this paper, the constrained optimization evolutionary algorithm is based on the quantum evolutionary alg...

Constrained Optimization with Evolutionary Algorithms:

( Global optimization is an essential part of any kind of system. Various algorithms have been proposed that try to imitate the learning and problem solving abilities of the nature up to certain level. The main idea of all nature-inspired algorithms is to generate an interconnected network of individuals, a population. Although most of unconstrained optimization problems can be easily handled w...

Constrained Evolutionary Optimization - the penalty function approach

Evolutionary Constrained Optimization for a Jupiter Capture

This investigation considers the optimization of multiple gravity assist capture trajectories in the Jupiter system combining the well known Differential Evolution algorithm with different classes of constraint handling techniques. The trajectories are designed to reach a desired target orbit around Jupiter with minimum fuel consumption while satisfying mission design constraints on maximum thr...