—This paper presents a new metamodel-assisted metaheuristic algorithm for optimisation problems involving computationally expensive simulations. The algorithm, called Global Prob...
Manydesign problems are solved using multiple levels of abstraction, wherea design at one level has combinatorially manychildren at the next level. A stochastic optimization metho...
Louis I. Steinberg, J. Storrs Hall, Brian D. Davis...
In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, timecost trade-off...
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...