This paper proposes a novel adaptive representation for evolutionary multiobjective optimization for solving a stock modeling problem. The standard Pareto Achieved Evolution Strat...
Mihai Oltean, Crina Grosan, Ajith Abraham, Mario K...
This paper introduces a novel scheme of improving the performance of particle swarm optimization (PSO) by a vector differential operator borrowed from differential evolution (DE)....
—We develop an algorithm aimed at estimating travel time on segments of a road network using a convex optimization framework. Sampled travel time from probe vehicles are assumed ...
Sebastien Blandin, Laurent El Ghaoui, Alexandre M....
This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not ne...
As the ever-increasing gap between the speed of processor and the speed of memory has become the cause of one of primary bottlenecks of computer systems, modern architecture system...