Optimization phd structural thesis

Optimization phd structural thesis

decisions regarding global structural behavior have the greatest impact on multi-objective project goals. Key words: constructability, conceptual structural design, structural optimization, construction, buildability, structural design tools Thesis Supervisor: Caitlin This thesis advances a recent work on the optimization of patterned surface structures used for architecture and structural engineering. On their own, well-designed surface structures--such as plates and shells--can be highly efficient, but by introducing specific aperture patterns, designers can further improve their potential for structural efficiency T1 - Structural Optimization of Wind Turbine Blades. AU - Sjølund, Jonas Heidemann. N1 - PhD supervisor: Professor, PhD, MSc, Erik Lund Department of Materials and Production Aalborg University. PY - /5/2. Y1 - /5/2. M3 - Ph.D. thesis. T3 - PhD Series, Faculty of Engineering and Science, Aalborg University

Optimization of Patterned Surface Structures

In this project, we want to investigate if deep learning methods can contribute in combinatorial optimization problems in particular if it can find any pattern among good solutions for a pickup and delivery problem and if so, then take advantage of it to lead the search toward even better solutions. Background: This project challenges your skill in algorithm design and your programming skill!

INF is highly recommended. Develop a Machine Learning based Hyper-heuristic algorithm to solve a pickup and delivery problem. A hyper-heuristic is a heuristics that choose heuristics automatically. Hyper-heuristic seeks to automate the optimization phd structural thesis of selecting, combining, generating or adapting several simpler heuristics to efficiently solve computational search problems [Handbook of Metaheuristics]. There might be multiple heuristics for solving a problem.

Heuristics have their own strength and weakness. In this project, we want to use machine-learning techniques to learn optimization phd structural thesis strength and weakness of each heuristic while we are using them in an iterative search for finding high quality solutions and then use them intelligently for the rest of the search.

Once a new information is gathered during the search the hyper-heuristic optimization phd structural thesis automatically adjusts the heuristics. This project addresses central challenges in climate and energy transition - How do we achieve more efficient transport systems to reduce emissions and improve land use? The goal of a sustainable logistics system is to improve profitability and reduce environmental impact for long-term performance.

A sustainable logistic need to consider economic, environmental, and social aspects that are essential for a logistics system. In addition, the future state of transportation systems in smart cities requires taking advantage of multimodal transportation that includes optimization phd structural thesis electric cars, boats, optimization phd structural thesis, trains, Robots, and drones, optimization phd structural thesis.

In this project, we aim at developing optimization models and artificial intelligence AI solutions for the problem of integrated multimodal transport planning, taking into account social, environmental, geographical and economical constraints. Transport planning is a complex combinatorial optimization problem and social, environmental and economic factors increases the complexity. This cross-disciplinary project is well positioned to solve this complex problem by combining expertise in optimization, AI, Logistics, and social science within urban development, governance and public perceptions.

This project can be divided into three different master projects. For details please see the project description! Advisor: Jan Rückmann. Maritime transportation is the obvious choice for heavy industrial activities where large volumes are transported over long distances. Norway is currently among the world's top 10 shipping nations in terms of tonnage, the number of vessels and the value of the fleet. Operational efficiency of maritime transportation can have a huge effect on consumers by reducing final product costs.

In this project, we address the ship routing and scheduling problem, which is one of the main problems in maritime transportation. In this problem, a shipping company has a set of contracted cargoes that it is committed to carry and there are also some spot cargoes available in the market.

Each cargo in the given planning period must be picked up at its port of loading, transported and then delivered to its corresponding discharging port.

There are time windows given, within which the loading of the cargoes must start, and there may also exist time windows for discharging. The shipping company can decide to serve some of the spot cargoes if they find it profitable.

This is a NP-hard problem and we are going to develop a powerful heuristic to solve the real size instances of the problem! Among various problems considered in supply chain logistics, pickup and delivery problem with time windows is one of the most practical one that has received a lot of attentions in the operation research community. Here we consider a shipping company, which operates a heterogeneous fleet of vehicles.

At a given point in time we consider a static and deterministic planning problem, consisting of determining how the fleet of vehicles should service a set of given requests.

The vehicles may be different in capacity, speed and cost, and compatibility for carrying certain request. If a request is assigned to a vehicle, the vehicle must pickup the request in its corresponding origin point pickup node and later deliver the request in its destination point delivery node.

All pickups and deliveries operations must be performed within a time interval that is specific to that operation for a given request. Pickup and delivery problem has many applications such as in postal service and food industry.

In this project, we are going to solve a very practical application of this problem which has more realistic assumptions than the original described version. Background: This project challenges your problem solving and programming skill as well as your skill in algorithm design! In this project, we address the multi-productmaritime inventory routing problem where each product can be produced and consumed in any number of ports.

During the planning horizon the level of each inventory of each product at each port must lie within fixed lower and upper limits at all times. Optimization phd structural thesis are lower and upper limits on the loaded and unloaded quantities. These operations generate fixed and variable costs, optimization phd structural thesis.

The multi-product maritime inventory routing problem consists of designing routes and schedules for the fleet in order to minimize the transportation and port costs, and to determine the quantities handled at each port call without exceeding the storage limits. We intend to mathematically formulate the problem and possibly find the upper and lower bounds. Since it is a NP-hard problem, to solve the optimization phd structural thesis size instances of the problem, we are going to develop a powerful heuristic!

Background: This project challenges your skill in Mathematical formulation and your programming skill! In a covering location problem, we seek location of a number of facilities on a network in such a way that the covered population is maximized.

A population is covered if at least one facility is located within a predefined distance of it. This predefined distance is often called coverage radius. The choice of this distance has a vital role and affects the optimal solution of the problem to a great extent. Covering location problem is of paramount importance in practice to locate many service facilities such as schools, parks, hospitals and emergency units.

In some practical cases, the population is moving during the planning horizon. In this project, we are going to develop a heuristic for the problem assuming the moving population.

Adaptive large neighbourhood search is a popular and widely used algorithm in the literature in solving combinatorial optimization phd structural thesis and in particular routing problems, optimization phd structural thesis. In this project, we are going to investigate the role of randomized components in this algorithm and provide deterministic alternatives that work as good as the original one, or even better!

Background: This project challenges your skill in algorithm design and your analytical and logical thinking! A location-routing problem may be defined as an extension to a multi depot vehicle routing problem in which there is a need to determine the optimal number and location of depots simultaneously with finding distribution routes. LRP is an NP-hard problem, as it encompasses two NP-hard problems facility location and vehicle routing.

Moreover, it is generally accepted that solving the two sub-problems separately often leads to sub-optimal solutions. LRP has many real-life applications such as in food and drink distribution, postal service, blood bank location, newspaper distribution, waste collection, and optimization phd structural thesis evacuation. In this project, we are going to solve a practical application of this problem which has more realistic assumptions than the original described version.

It is an iterative method and in every iteration it uses f x and f' x. Halley's method uses f xf' x and f'' x at every iteration. In a textbook on iterative methods the optimization phd structural thesis claims that Halley's method is the most rediscovered method.

The purpose of this project is to explore the different ways to derive the method and follow the historical thread and to explore the algorithmic consequences of the different derivations of Halley's method. For more information on the project contact the supervisor professor Trond Steihaug. When we say that one algorithm is more efficient than another algorithm in optimization, we often compare number of arithmetic operations. However, the amount of memory and memory access is often as important.

In this project you will test different data structures with different memory access. The project requires optimization phd structural thesis programming.

This topic covers the application of several solution methods for nonlinear optimization problems. Nonlinear Optimization or Programming models can be used for the modelling, description and solution of real-life application from a huge variety of areas; among them are finance, economics, production planning, optimization phd structural thesis, trajectory calculation and others.

In dependence on the chosen application and the recommended solution method the corresponding master thesis project might include modelling and numerical solution aspects. The use of mathematical optimization methods in finance is common-place and a continuously developing vivid area of research, optimization phd structural thesis. These methods are used for many different tasks: for pricing financial products, estimating risks, determining hedging strategies, optimization phd structural thesis, and many others.

The goal of this project is to study how optimization techniques - such as linear, quadratic, optimization phd structural thesis, and nonlinear programming, robust optimization, dynamic programming, integer programming, and others - can be used in the framework of mathematical finance.

In this project the candidate will study recent models from mathematical finance which are using mathematical optimization techniques. Furthermore, corresponding solution methods will then be applied numerically to some particularly chosen models. The latter part refers to efficient implementation of solution techniques and calculating numerical solutions.

Investors in charge of selecting the assets to constitute a portfolio, will typically use the expected return as a measure of the expected value, and the variance as a measure of the risk.

To keep operational costs down, the investors may impose certain constraints on the portfolio selection. For instance, they may require that the volume of any selected asset must be at least a given fraction of the total portfolio.

In this thesis, the candidate will study mathematical models and efficient solution techniques for such problems. In many industrial applications of network flow problems, such as oil refining and pipeline transportation of natural gas, the composition of the flow is of interest. At the source nodes, flow of different compositions qualities is supplied. Flow from the sources is blended at intermediate nodes, optimization phd structural thesis to as pools.

The blending operation is linear, in the sense that one flow unit containing e, optimization phd structural thesis. Flow from the pools is blended linearly at the terminals, where bounds on the resulting quality apply.

Unit purchase costs at the sources and sales revenues at the terminals are defined, and the problem is to find a flow assignment to the network, such that quality bounds are respected, and total net profit is maximized.

It has been shown that this problem, frequently referred to as the pooling problem, is strongly NP-hard, even if there is only one pool. The same is true if there is only one quality parameter e. CO2 subject to upper bounds. In the industry, there is a request for fast solution methods, which does not seem realistic for general instances of realistic size. The focus of the current project is to find fast, possibly inexact, solution methods for the pooling problem.

It is also a goal to identify special instance classes that can be solved fast, and to evaluate algorithms for such instances experimentally.

The successful candidate has good programming skills and some background in optimization. Advisor: Dag Haugland. This project considers how an order market might evolve over a fairly short period - say, during a day.

Considered is a stylized market for one homogenous, perfectly divisible good.

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Structural Optimization of Wind Turbine Blades — Aalborg University's Research Portal

Sep 10,  · Optimization Phd Structural Thesis There are students who Optimization Phd Structural Thesis have experienced disappointment with the college paper writing service they hired due to incompetent and uncommitted writers. So, before you pay to write essay Optimization Phd Structural Thesis for you, make sure you have taken necessary steps Optimization Phd Structural Thesis Topology optimization is a tool for nding a domain in which material is placed that optimizes a certain objective function subject to constraints. This thesis considers topology optimization for structural mechanics problems, where the underlying PDE is derived from linear elasticity Structural behavior relationships, equilibrium and compatibility, are treated as explicit equality constraints and the problem solved as a large scale nonlinear mathematical programming problem. In contrast to current methods of optimization where analysis and design are separated into two distinct phases, the integrated approach does not