SDE: a stochastic coding differential evolution for global optimization
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Multi Agent Collaborative Search based on Tchebycheff decomposition
Computational Optimization and Applications
Differential evolution methods based on local searches
Computers and Operations Research
Evolutionary annealing: global optimization in measure spaces
Journal of Global Optimization
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In this paper, we define a discrete dynamical system that governs the evolution of a population of agents. From the dynamical system, a variant of differential evolution (DE) is derived. It is then demonstrated that, under some assumptions on the differential mutation strategy and on the local structure of the objective function, the proposed dynamical system has fixed points toward which it converges with probability one for an infinite number of generations. This property is used to derive an algorithm that performs better than standard DE on some space trajectory optimization problems. The novel algorithm is then extended with a guided restart procedure that further increases the performance, reducing the probability of stagnation in deceptive local minima.