Multi-Objective Evolutionary Algorithms (MOEAs) and transport simulators have been widely utilized to optimise traffic signal timings with multiple objectives. However, traffic simulations require much processing time and ...

Memetic Computing (MC) is a discipline which studies optimization algorithms and sees them as structures of operators, the memes. Although the choice of memes is crucial for an effective algorithmic design, special attention ...

The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the ...

Differential Evolution (DE) is a popular population-based continuous optimization algorithm that generates new candidate solutions by perturbing the existing ones, using scaled differences of randomly selected solutions ...

Abstract Challenging optimisation problems are abundant in all areas of science and industry. Since the 1950s, scientists have responded to this by developing ever-diversifying families of ‘black box’ optimisation algorithms. ...

Differential evolution (DE) has become a prevalent tool for global optimization problems since it was proposed in 1995. As usual, when applying DE to a specific problem, determining the most proper strategy and its associated ...