Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic
algorithm for solving the resource constrained project scheduling problem (RCPSP). To the …

Many decisions in a machine learning (ML) pipeline involve nondifferentiable and
discontinuous objectives and search spaces. Examples include feature selection, model …

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the
motion of virtual particles within a multidimensional space. The particles explore the space …

The set covering problem is a formal model for many practical optimization problems. In the
set covering problem the goal is to choose a subset of the columns of minimal cost that …

The set covering problem belongs to the combinatorial optimization problems, whose
complexity is exponential theoretically established as NP-complex problems. Consists in …

Phase Change Memory (PCM) and spin-transfer torque random access memory (STT-RAM)
are emerging as new memory technologies to replace DRAM and NAND flash that are …

The set cover problem, belongs to the branch of combinatorial optimization problems, whose
complexity is exponential theoretically established as NP-complex problems. Consists in …

Evolutionary algorithms are optimization methods commonly used to solve engineering and
business optimization problems. The parameters in evolutionary algorithm must be perfectly …

Abstract The Software Project Scheduling Problem is a specific Project Scheduling Problem
present in many industrial and academic areas. This problem consists in making the …