The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …

Benchmarking heuristic algorithms is vital to understand under which conditions and on
what kind of problems certain algorithms perform well. In most current research into heuristic …

This paper addresses the increasing complexity of challenges in the field of continuous
nonlinear optimization by proposing an innovative algorithm called information acquisition …

Numerical optimization for the inverse design of photonic structures is a tool that is providing
increasingly convincing results—even though the wave nature of problems in photonics …

A method of heuristically solving large traveling salesman problems is suggested, where a
dramatic computational speedup is guaranteed. A specific genetic algorithm is the solver …

Improvement of particle swarm optimization (PSO) is relevant to solving the inherent local
optima and premature convergence problem of the PSO. In this paper, a novel improvement …

Digital twins need efficient methodologies to design maintenance strategies for decision-
making purposes. Recently, a methodology coupling computational simulation and …

This paper presents a new chance-constrained optimization (CCO) formulation for the bulk
carrier conceptual design. The CCO problem is modeled through the scenario design …

In Artificial Intelligence, there is an increasing demand for adaptive models capable of
dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems …

Microfluidic technology, which involves the manipulation of fluids in microchannels, faces
challenges in channel design and performance optimization due to its complex, multi …