By using renewable biomass, the advancement in biofuel production through a smart
inspection production framework is a crucial substitute to fossil fuels which support …

This paper proposes a coordinated electric bus (EB) charging scheduling approach for
hybrid charging stations that support plug-in charging and battery-swapping simultaneously …

A microgrid's energy management system (EMS) is typically formulated as a deterministic
optimization problem. However, more risks and uncertainties are emerging due to the …

Scheduling decision-making is often calculated and implemented using unreliable or
inaccurate data from process networks, therefore infeasibilities and inconsistencies in the …

Designing a stochastic supply chain is challenging because demand is often partially
observable or unknown in advance. This paper presents an alternative approach to address …

Modeling and optimization of large-scale refinery scheduling problems is challenging
because of their complexity and size. Herein, we propose a mathematical model to …

This study presents a methodology that makes use of Deep Recurrent Q-Learning to
develop an agent that acts as an online scheduler for flow-shop or job-shop batch plants …

This thesis focus on the research of the DC microgrid following two operation models: grid-
connected mode, and off-grid mode including the islanded and isolated modes. The aim of …

Using deterministic values of input variables is desirable for process design. However, some
of these input variables may present uncertainty, which may drive the designed process to …

The deregulation of electricity markets has led to an increased demand for optimizing market
bidding strategies. Consequently, this research focuses on the optimization of bidding …