This paper introduces a new design methodology (we call it "innovization") in the context of finding new and innovative design principles by means of optimization techni...
: Evolutionary multi-objective optimization (EMO) methodologies have been amply applied to find a representative set of Pareto-optimal solutions in the past decade and beyond. Alth...
Nadir point plays an important role in multi-objective optimization because of its importance in estimating the range of objective values corresponding to desired Pareto-optimal s...
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
This paper introduces a metric that measures symmetry in tree graphs, which allows for a statistical characterization of GP solutions by their architectural "shapes." A ...
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
Garbage collection can be a performance bottleneck in large distributed, multi-threaded applications. Applications may produce millions of objects during their lifetimes and may i...
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...