An Integrated Approach towards Predictive Maintenance on Land Drilling Rigs

The drilling industry faces the challenge of moving away from conventional maintenance strategies to maximise operational efficiency. This thesis introduces a holistic approach to land drilling rig Predictive Maintenance (PdM), integrating component maintenance into system-level decision-making. By taking the operations of the whole system into...

Solving Large-Scale Dynamic Collaborative Vehicle Routing Problems: An Auction-Based Multi-Agent Approach

The freight transportation sector is one of the major contributors to air pollution. An important way to reduce emissions consists of collective route planning. Although unloaded trips and inefficient routes could not always be prevented by individual carriers, more efficient operations could often be obtained if multiple carriers collaborate by...

Agent-based Modelling and Simulation of Airport Terminal Operations under COVID-19-related Restrictions

The worldwide COVID-19 pandemic has had a tremendous impact on the aviation industry, with a reduction in passenger demand never seen before. To minimise the spread of the virus and to gain trust from the public in the airport operations' safety, airports implemented measures, e.g., physical distancing, entry/exit temperature screening and more....

Multi-Agent Pickup-and-Delivery in a Distributed Baggage Handling System

Baggage handling systems in airports are generally over-designed and only need to work at full capacity for a couple of months during their lifetime. To cope with varying demand, flexible baggage handling systems are being developed which use Automated Guided Vehicles (AGV) to handle a required capacity. These AGVs transport bags throughout the...

The performance Impact of Communication Failure in BlocksWorld for Teams

Multi-agent systems often communicate to perform better at their tasks. However, messages sometimes get lost after sending, and the communication is disrupted. This paper looks into the effects of messages having a chance of not arriving with an agent using the Blocks World for Teams simulation environment. The environment uses agent teams...

Fault-tolerance in decentralized motorway traffic management

In the Dutch motorway traffic management (MTM) system used by Rijkswaterstaat, a central system and multiple outstations alongside the road communicate with each other to keep highways safe. This makes the MTM system a form of distributed flow control system. However, Rijkswaterstaat faces 2 problems with regards to traffic control: the control...

Decentralized Combinatorial Auctions for Dynamic and Large-Scale Collaborative Vehicle Routing

While collaborative vehicle routing has a significant potential to reduce transportation costs and emissions, current approaches are limited in terms of applicability, unrealistic assumptions, and low scalability. Centralized planning generally assumes full information and full control, which is often unacceptable for individual carriers....

Collaborative Vehicle Routing when Agents have Mixed Information Sharing Attitudes

The transportation market requires collaboration to improve efficiency and reduce emissions. Individual carriers, however, might be hesitant to share their private information on a transportation platform. Although a few articles have investigated the value of information sharing, they assume identical behaviour of all carriers. In practice,...

Feasibility Study of LUFAR

With the steady increase in space missions, enabled through technological advances and increase of commercialisation within the space flight industry, both more and increasingly complex missions can be designed for space. To this end, the Lunar Zebro project competes within this field through its small lunar rover design, drastically decreasing...

Multi-Agent Deep Reinforcement Learning for Automated Highway Driving

Recent advances in Deep Reinforcement Learning have sparked new interest in many different research topics, including Automated Highway Driving where agents model autonomous vehicles. The main advantage of Deep Reinforcement Learning is that the training algorithm is adaptable to its environment. In highway driving, researchers often simplify...

Decentralized Collision Avoidance of Multi-Agent Systems in 3-Dimensional Space

Multi-Agent Systems, often referred to a network of loosely connected autonomous units, are widely used to model the dynamics of crowds, vehicles, robots and swarms in traffic management, biological environment, distributed control and communication technologies. Recently, the study of multi-agent systems is rapidly growing due to the beneficial...

Distributed Control Design of District Heating Networks

In The Netherlands, the current heat energy system accounts for 44% of the primary energy usage and relies almost entirely on fossil fuels such as natural gas. To meet the Paris Climate Agreement goals, 4th Generation District Heating (4GDH) networks are expected as sustainable heat energy system solution. The concept relies on optimally...

Network-Decentralized Control with Collision Avoidance for Multi-Agent Systems

An often preferred method to control a multi-agent system is by a network-decentralised controller. Network-decentralised means that each agent only has knowledge about its own state and the state of its neighbouring agents. In this thesis the multi-agent system consists of holonomic robots moving in a 2-dimensional configuration space. Each...

Evaluating a Cognitive Agent-Orientated Approach for the creation of Artificial Intelligence in StarCraft

In this thesis a cognitive multi-agent system is developed for the real-time strategy game StarCraft: Brood War using GOAL, a language developed at the Delft University of Technology. StarCraft provides various challenges to GOAL that it has not faced before in terms of complexity and quantity of agents. A connector is required for GOAL to...