The vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem,
and many models and algorithms have been proposed to solve the VRP and its variants …

The traveling salesman problem (TSP) is one of the best-known combinatorial optimization
problems. Many methods derived from TSP have been applied to study autonomous vehicle …

Designing trajectories in dynamically complex environments is challenging and easily
becomes intractable. Recasting the problem may reduce the design time and offer global …

In this paper, we present a technique to tune the reinforcement learning (RL) parameters
applied to the sequential ordering problem (SOP) using the Scott–Knott method. The RL has …

The object population in the space around the Earth is subject to increase. With the
advancements in sensor capabilities, it can be expected that, at the same time, more of …

Low-thrust many-revolution trajectory design and orbit transfers are becoming increasingly
important with the development of high specific impulse, low-thrust engines. Closed-loop …

Reinforcement learning is an important technique in various fields, particularly in automated
machine learning for reinforcement learning (AutoRL). The integration of transfer learning …

Travelling salesman problem (TSP) is one of the most famous problems in graph theory, as
well as one of the typical nondeterministic polynomial time (NP)‐hard problems in …

Reinforcement learning is a crucial area of machine learning, with a wide range of
applications. To conduct experiments in this research field, it is necessary to define the …

Spacecraft trajectory design is critical to successful space missions, particularly with the
increasing number of spacecraft and mission complexity. Satellite constellation deployment …