Model-based Integrated Planning and Control of Autonomous Vehicles using Artificial Potential Fields

Navigation systems in an Autonomous Vehicles (AV) can be divided into two parts: a path planning block which takes in the environmental data and rules to design a collision-free obstacle and a vehicle control and tracking block which generates actuator inputs for the AV to follow the reference path generated by the path planning block. Each task...

Modelling Hydrogen in Power Systems: Optimisation for Investment and Operational Models

The energy transition is one of the major challenges of the 21st century, impacting the way energy is generated, conserved and consumed. Energy generation becomes more and more decentralised, intermittency and fluctuations suddenly are becoming topics of interest within day-to-day life and energy system operators are facing many new obstacles...

IAF Assignment Optimization for Amsterdam Airport Schiphol

During the COVID-19 pandemic people living close to the airport got accustomed to less flights, and therefore less noise disturbance. Now the amount of traffic is increasing again and so is the noise disturbance. For this research specifically the optimizing task of distributing of arriving aircraft over the IAF is addressed, as often the...

Integrating Predictive and Optimization Model for Intelligent Schedule Management based on Real Time ETA Information: A Concept of Machine Learning and Exact Solution in Petrochemical Loading Facility

This study addresses the truck rescheduling problem as the consequence of uncertain arrival time. It proposes an integrated system of predictive model powered by machine learning algorithm and exact optimization model such that it is distinct from most existing literatures in this domain. The uncertainty of truck arrival time is captured as...

Scheduling and Assignment of Fighter Pilot Training Missions: A Two-Stage Optimization Approach Towards Increasing Personnel Readiness in the Armed Forces

Military fighter pilots spend most of their working hours performing training missions, simultaneously carried out by multiple pilots with different qualifications. Scheduling these missions is typically done manually, which is a time-consuming task resulting in far from optimal schedules. This study proposes a model that schedules three types...

Scheduling optimization in a refinery for vegetable oils

A mathematical model has been developed to determine the timing of the tasks that can be performed on a variety of units to produce a variety of end states and to monitor the flow of the material through the network. The mathematical model is based on the work of Kondili et al. (1993) and is extended with the ability to monitor and restrict the...

Training Neural Networks with Discrete Optimization Solvers

Recent work has shown potential in using Mixed Integer Programming (MIP) solvers to optimize certain aspects of neural networks (NN). However little research has gone into training NNs with MIP solvers. State of the art methods to train NNs are typically gradient-based and require significant amounts of data, computation on GPUs and extensive...

Planning and Control of Multiple Mobile Robots for Intralogistics: an optimization-based reordering strategy

In this thesis we consider multiple Automated Guided Vehicles (AGVs) navigating a common workspace to fulfill intralogistics tasks, typically formulated as the Multi-Agent Path Finding (MAPF) problem. To keep plan execution deadlock-free, one approach is to construct an Action Dependency Graph (ADG) which encodes the ordering of AGVs as they...

David and the vegetable factory: A Two-stage Optimization Model for Generating a Vegetable Factory's Facility Layout Using the Gradient Descent Approach

In this thesis a two-stage model is proposed, combining the idea of a two-stage model from Anjos and Vieira [1] with a gradient descent approach, much like proposed in Sikaroudi and Shahanaghi [42], in order to solve the facility layout problem for problems consisting of 8 and 12 departments . This method was chosen after analyzing the criteria...

MIPLIB Truckload PDPTW Instances Derived from a Real-World Drayage Case

This paper describes five sets of 33 Mixed Integer Problem instances each, for a total of 165 instances, derived from a real-world full-truckload pick-up and delivery problem with time windows at the Port of Rotterdam. These instances represent 33 individual days of data encompassing 65 jobs and 40 trucks. We report, in this paper, on the...

The Dynamic Dial-a-Ride Problem with Time Windows in a Competitive Multi-Company Environment

Door-to-door transportation for elderly and disabled people is for many governments an important instrument to increase the mobility of this group of people. Many issues arise in the implementation of such a system, which is often modeled as the Dynamic Dial-a-Ride System with Time Windows (DDARPTW). One of those issues is that taxi companies...