With sufficient layers, enough training data, enough time, and often a custom tailored architecture, modern deep learning methods can be extremely successf...

A new mathematical model for stochastic short-term optimization of mining complexes is presented that simultaneously optimizes the short-term extraction sequ...

This paper presents the application of adaptive simultaneous stochastic optimization with a representative branching framework to generate the strategic pl...

We analyze a differential game with spatially distributed controls to study a multiregional transboundary pollution problem. The dynamics of the state variab...

Cities are facing severe traffic-related problems causing emission thresholds to be exceeded. All around the world, city center access restriction policies a...

This paper presents a linear mixed-integer formulation to solve the short-term unit commitment problem. It determines the pair of maximum efficiency points o...

Mathematical models of energy-economy-environmental systems (E3) provide a rational framework for exploring the effects of energy and climate policies and su...

The introduction of renewable energy sources (RES) changes the shape of an electricity system's supply curve. In a perfectly competitive market, this causes ...

The deepening penetration of renewable power generation is challenging how the minute balancing of supply and demand is carried out by power system operators...

We analyze an endogenous growth model with non-constant discounting and a negative externality of growth on utility. With a decreasing rate of impatience, ...

We study the time evolution of a vertically and horizontally differentiated oligopolistic industry, where firms compete in quantity and are divided into gr...

Multi-agent reinforcement learning has made significant progress in recent years, but it remains a hard problem. Hence, one often resorts to developing lea...

We are interested in blackbox optimization for which the user is aware of monotonic behaviour of some constraints defining the problem. That is, when incr...

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, ...

This is a two-part work. In Part I, low-cost and representative reduced-fidelity models of two versions of the HYDROTEL hydrological model are constructed, u...

Dealing with computationally-intensive calibration processes is still common in distributed hydrological modelling despite the computing power growth. Comput...

The open-pit mine production scheduling problem aims to optimize the net present value of a mining asset. Several solution methods have been proposed to find...

Microgrid, a promising component of smart grid, will potentially yield a free electricity market. This paper proposes a novel construction for a community mi...

The paper combines two major contemporary systems and control methodologies to obtain a unique $\epsilon$-Nash equilibrium for optimal execution problem...

For the past few years, the mining industry has seen a lot of operational changes. Digitalization and automation of many processes have paved the way for an ...