Evolutionary algorithms (EAs) are increasingly being applied to solve real-parameter optimization problems due to their flexibility in handling complexities such as non-convexity,...
Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joyd...
The algorithmic framework developed for improving heuristic solutions of the new version of deterministic TSP [Choi et al., 2002] is extended to the stochastic case. To verify the...
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
In this paper we introduce a new general framework for set covering problems, based on the combination of randomized rounding of the (near-)optimal solution of the Linear Programm...
Recently, a new iterative optimization framework utilizing an evolutionary algorithm called "Prototype Optimization with Evolved iMprovement Steps" (POEMS) was introduced...