Should automation be regulated? This paper studies optimal tax of robot and regulation of automation. A job assignment model is embedded into a Mirrleesian tax problem. A task may either be assigned to the robot or one type of labors, which naturally determines the automation rate. The robot can...

This paper proposes a branch-and-bound algorithm (B&B) for the proactive scheduling problem, which incorporates a degree of anticipation for variability in practical projects. First, the resource-constrained proactive scheduling model is formulated. Second, solving its resource-unconstrained...

This research devises an initial attack plan to combat wildfires that break out in wildland-urban interfaces. To be eligible for such a plan, the landscape must have been previously mapped and modelled concerning spatial and topographic data and fuel levels. Thus, when ignition occurs, one can...

Bayesian optimization (BO) is increasingly employed in critical applications such as materials design and drug discovery. An increasingly popular strategy in BO is to forgo the sole reliance on high-fidelity data and instead use an ensemble of information sources which provide inexpensive...

Ensemble techniques are frequently encountered in machine learning and engineering problems since the method combines different models and produces an optimal predictive solution. The ensemble concept can be adapted to deep learning models to provide robustness and reliability. Due to the growth...

With the advent of Big Data, managing large-scale portfolios of thousands of securities is one of the most challenging tasks in the asset management industry. This study uses an evolutionary multi objective technique to solve large-scale portfolio optimisation problems with both long-term listed...

This article proposes a new, more efficient quantum algorithm for portfolio optimization and uses quantum combinatorial optimization (QCO) techniques. The recent construction developed in 2021 has sparked the field of financial portfolio optimization through the Quantum Walk Optimization...