Abstract Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been
successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally …

Learning heuristics for vehicle routing problems (VRPs) has gained much attention due to
the less reliance on hand-crafted rules. However, existing methods are typically trained and …

The recent end-to-end neural solvers have shown promise for small-scale routing problems
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …

Learning to solve vehicle routing problems (VRPs) has garnered much attention. However,
most neural solvers are only structured and trained independently on a specific problem …

To reduce the waste of fresh foods, one of the e-commerce companies in South Korea
utilizes lateral transshipment in the network of online platforms and offline shops, which is …

Efficient specialized vehicle cooperative scheduling is significant for airport operations,
particularly during times of high traffic, which reduces the risk of flight delays and increases …

This paper presents a systematic review on reinforcement learning approaches for
combinatorial optimization problems based on real-world industrial applications. While this …

Abstract The goal of Railcar Itinerary Optimization in Marshalling Yards (RIO-MY) is to
achieve an effective integrated operation plan for both train shunting operations and train …

To reduce airport operational costs and minimize environmental pollution, an increasing
number of airports are transitioning from fuel-powered to electric ground-handling vehicles …

Digital technologies have become instrumental in every industry, enabling a multitude of
benefits. Aviation is one of the industries in which the fourth industrial revolution is taking …