A Q-learning based multi-strategy integrated artificial bee colony algorithm with application in unmanned vehicle path planning

Artificial bee colony (ABC) is a prominent algorithm that offers great exploration capabilities among various meta-heuristic algorithms. However, its monotonous and one-dimensional search strategy limits its searching performance in the solving process. Thus, to address this issue, a Q-learning based multi-strategy integrated ABC algorithm ...

Experimental Parameter Identification of Nonlinear Mechanical Systems via Meta-heuristic Optimisation Methods

Meta-heuristic optimisation algorithms are high-level procedures designed to discover near-optimal solutions to optimisation problems. These strategies can efficiently explore the design space of the problems; therefore, they perform well even when incomplete and scarce information is available. Such characteristics make them the ideal...

Comparison of Different Optimization Techniques in Electron Lens Design

To design electron lens systems, applying a fully automated optimization routine has not yet been feasible, especially for the case where the optimization has many free variables of the lens system, such as all parameters that define the geometry of the lens electrodes and the voltage of each electrode. Hence, the study of the implementation of...

Solving a flexible resource-constrained project scheduling problem for an e-grocery fulfilment centre: a meta-heuristic approach: Master thesis Aerospace Engineering

The demand for online shopping has grown tremendously in the last couple of years. Picnic, a major player in the online grocery industry, is struggling to achieve long-term growth within its current operations. Scheduling and planning are key drivers for maintaining operational efficiency. The Fulfilment Centre (FC) and...

An improved Tabu Search for optimising the configuration of an agent-based simulation model of a novel security checkpoint

The major international airport, Amsterdam Airport Schiphol, is redesigning its security checkpoints for 2024, for which a novel type of security checkpoint configuration is considered. In this redesign, one seeks to find the optimal checkpoint configuration; however, this remains non-trivial. The checkpoint configuration problem requires a...

Modeling System Behaviour from Log Analysis Using Meta-Heuristic Search

Understanding the behaviour of a software system plays a key role in its development and maintenance processes. Unfortunately, accurate and concise models are not always available during development, due to the rapid changes in the structure and scale systems may undergo during this phase. Finite State Machines (FSM) are a natural and prevalent...

A data-driven heuristic decision strategy for data-scarce optimization: with an application towards bio-based composites

Algorithmic optimization is a viable tool for solving complex materials engineering issues. In this study, a data-scarce Bayesian optimization model was developed to research the composition of bio-based composites. The proof-of-concept program adjusts the natural materials' weight ratios to optimize towards user-defined mechanical properties....

Hybrid truss layout optimization for generating multiple design alternatives

As of writing this thesis little research has been done in truss layout optimization for multiple design alternatives. A hybrid scheme is proposed in which the fast gradient-based search of the Ground Structure Method (GSM) is employed for the search of optimal topology and size, while a population-based meta-heuristic algorithm explores the non...

Land subsidence susceptibility mapping using persistent scatterer SAR interferometry technique and optimized hybrid machine learning algorithms

In this paper, land subsidence susceptibility was assessed for Shahryar County in Iran using the adaptive neuro-fuzzy inference system (ANFIS) machine learning algorithm. Another aim of the present paper was to assess if ensembles of ANFIS with two meta-heuristic algorithms (imperialist competitive algorithm (ICA) and gray wolf optimization ...

Meta-heuristic improvement of order picking efficiency: Exploiting cross-order similarity in a goods-to-person warehouse

This research aims at determining a suitable order release strategy for a warehouse featuring a shuttle-based storage and retrieval system with multiple goods-to-person picking workstations. These picking workstations facilitate efficient picking; however, current release strategies do not take similarity between orders into account, while this...

A variant of the split vehicle routing problem with simultaneous deliveries and pickups for inland container shipping in dry-port based systems

In this paper, we will study a typical problem in inland container shipping, concerning the barge transportation of maritime containers between a dry port and a set of seaport terminals. The barges depart from the dry port and visit a set of sea terminals, where containers need either to be dropped off or picked up. The goal is to achieve...

Automated dig-limit optimization through simulated annealing