Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...

A methodology for developing evidence-based optimization models in humanitarian logistics

The growing need for humanitarian assistance has inspired an increasing amount of academic publications in the field of humanitarian logistics. Over the past two decades, the humanitarian logistics literature has developed a powerful toolbox of standardized problem formulations to address problems ranging from distribution to scheduling or...

An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks

Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling...

Mixed-Integer Nonlinear Programming for Energy-Efficient Container Handling: Formulation and Customized Genetic Algorithm

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling...

Hybrid Berth Allocation for Bulk Ports with Unavailability and Stock Level Constraints

Berth allocation is fundamental to port-related operations in maritime shipping. Port managers have to deal with the increasing demands either by expanding the terminals or by improving efficiency to maintain competitiveness. Port expansion is a long-term project, and it requires much capital investment. Thus, the question of how to enhance...

Hierarchical Model Predictive Control for on-Line High-Speed Railway Delay Management and Train Control in a Dynamic Operations Environment

In practice, the operation of high-speed trains is often affected by adverse weather conditions or equipment failures, which result in delays and even cancellations of train services. In this article, a novel two-layer hierarchical model predictive control (MPC) model is proposed for on-line high-speed railway delay management and train...

Passenger-centered vulnerability assessment of railway networks

The performance and behaviour of critical infrastructure in case of disruptions is an important topic and we are still lacking of insights. Due to disruptions, infrastructure becomes unavailable and may force the trains and passengers to adapt. In this paper, we introduce a problem of railway network vulnerability from the perspective of...

Model Reduction and Outer Approximation for Optimizing the Placement of Control Valves in Complex Water Networks

The optimal placement and operation of pressure control valves in water distribution networks is a challenging engineering problem. When formulated in a mathematical optimization framework, this problem results in a nonconvex mixed integer nonlinear program (MINLP), which has combinatorial computational complexity. As a result, the considered...

Dynamic Ramping Model Including Intraperiod Ramp-Rate Changes in Unit Commitment

The growing increase of renewable generation worldwide is posing new challenges for a secure, reliable and economic operation of power systems. In order to face the uncertain and intermittent production of renewable sources, operating reserves must be allocated efficiently and accurately. Nowadays, these reserves are mainly assigned to thermal...