A review of asset management literature on multi-asset systems

This article gives an overview of the literature on asset management for multi-unit systems with an emphasis on two multi-asset categories: fleet (a system of homogeneous assets) and portfolio (a system of heterogeneous assets). As asset systems become more complicated, researchers have employed different terms to refer to their specific problems. With an objective to facilitate readers in searching conducive studies to their interests, this paper establishes a novel classification scheme for multi-unit systems in accordance with essential features such as diversity of assets and intervention options. Moreover, discerning differences in characteristics between cross-component and cross-asset interactions, we select three types of potential multi-component dependencies (performance, stochastic, and resource) and extend their notions to be applicable to multi-asset systems. The investigation into these dependencies enables the identification of problems that could exist in real industrial settings but are yet to be determined in academia. Ultimately, we delve into modelling approaches adopted by previous researchers. This comprehensive information allows us to offer the insights into the current trends in multi-asset maintenance. We expect that the output of this review paper will not only stress research gaps on multi-asset systems, but more importantly help systematise future studies on this aspect

Two Centuries of Commodity Cycles - Dynamics of the Metals & Mining Industry in light of Modern Portfolio Theory

This thesis explores the application of Markowitz' Modern Portfolio Theory onto 220 years of financial returns for 13 metals and 21 poly-metallic ore types. The interdisciplinary research shows that poly-metallic ores can be described as naturally occurring portfolios that were diversified by natural geological processes. Safest and optimal portfolios for metals and ores can be computed for different time horizons using portfolio optimization algorithms. Results for optimized ore portfolios are thereby subject to geological constraints. The study revealed that commodity cycles last between six and twenty years and exhibit clockwise and counterclockwise motions in the risk-return framework. The cycle length differences for clockwise cycles are statistically significant and thus specific to all investigated metals and ores. By incorporating novel cycle parameters into decision making tools it is suggested that current industry decisions for resource development can be improved. Insights into the performance of metals and ores through the industrial cycles, as well as into the frequency of profitable super cycles can assist Metals & Mining executives in strategic planning and investment.:Introduction 1 Data 3 Metals & ore types studied 5 2.1 Metals.......................................... 5 2.2 Ore types ........................................ 5 2.3 Prices .......................................... 10 2.4 Summary ........................................ 12 II Analysis 13 3 Modern Portfolio Theory 15 3.1 Overview ........................................ 15 3.2 Definitions........................................ 15 3.3 Assumptions ...................................... 17 3.4 Discussion & Conclusion................................ 18 4 Poly-metallic ores as natural portfolios 19 4.1 Objectives........................................ 19 4.2 Results.......................................... 19 4.3 Summary & Discussion................................. 24 4.4 Conclusion ....................................... 25 5 Static portfolio optimization 27 5.1 Objectives........................................ 27 5.2 Assumptions ...................................... 27 5.3 Results.......................................... 27 5.4 Summary & Discussion................................. 31 5.5 Conclusion ....................................... 32 6 Dynamic portfolio optimization 33 6.1 Assumptions ...................................... 33 6.2 Results.......................................... 34 6.3 Summary & Discussion................................. 44 6.4 Conclusion ....................................... 45 7 Commodity cycles & metal assets 47 7.1 Commodity cycles ................................... 47 7.2 Commodity cycle observations ............................ 54 7.3 Summary ........................................ 76 7.4 Discussion........................................ 77 7.5 Conclusion ....................................... 78 III Application 81 8 Commodity cycles & resource development strategies 83 8.1 The timing of mine development and mining start-up................ 83 8.2 Lead times from discovery to operation........................ 88 8.3 Exploration....................................... 89 8.4 Project valuation considerations............................ 91 8.5 Summary & Discussion................................. 92 8.6 Conclusion ....................................... 93 9 Industrial cycles & modern history 95 9.1 The Metal Markets Indicator-MMI ......................... 95 9.2 The Metal Markets Indicator & the economy .................... 97 9.3 The MMI & military conflict ............................. 105 9.4 MMI cyclicality..................................... 115 9.5 Summary & Discussion................................. 122 9.6 Conclusion ....................................... 123 10 Industrial cycles & metal performance 125 10.1 Methodology ...................................... 125 10.2 Metal performance during technological epochs ................ 126 10.3 Discussion........................................ 133 10.4 Conclusion ....................................... 137 11 Industrial cycles & ore type preferences 139 11.1 Coal Age ........................................ 139 11.2 Oil Age ......................................... 142 11.3 Atomic Age....................................... 144 11.4 Discussion........................................ 146 11.5 Conclusion ....................................... 150 12 Industrial cycles & ore provinces 151 12.1 Ore genetic models and industrial cycles....................... 151 12.2 Ore geology and geography .............................. 154 12.3 Ore provenances and mining technology ....................... 156 12.4 Discussion........................................ 157 12.5 Conclusion ....................................... 157 13 The state and future of the M&M Industry 159 13.1 The current state.................................... 159 13.2 The dawn of a new Industrial Age .......................... 163 13.3 The future........................................ 164 13.4 Summary & Discussion................................. 167 13.5 Conclusion ....................................... 168 14 Summary 169 15 Conclusion 171 IV Appendix 173 Bibliography 233 Index 24

From metaheuristics to learnheuristics: Applications to logistics, finance, and computing

Un gran nombre de processos de presa de decisions en sectors estratègics com el transport i la producció representen problemes NP-difícils. Sovint, aquests processos es caracteritzen per alts nivells d'incertesa i dinamisme. Les metaheurístiques són mètodes populars per a resoldre problemes d'optimització difícils en temps de càlcul raonables. No obstant això, sovint assumeixen que els inputs, les funcions objectiu, i les restriccions són deterministes i conegudes. Aquests constitueixen supòsits forts que obliguen a treballar amb problemes simplificats. Com a conseqüència, les solucions poden conduir a resultats pobres. Les simheurístiques integren la simulació a les metaheurístiques per resoldre problemes estocàstics d'una manera natural. Anàlogament, les learnheurístiques combinen l'estadística amb les metaheurístiques per fer front a problemes en entorns dinàmics, en què els inputs poden dependre de l'estructura de la solució. En aquest context, les principals contribucions d'aquesta tesi són: el disseny de les learnheurístiques, una classificació dels treballs que combinen l'estadística / l'aprenentatge automàtic i les metaheurístiques, i diverses aplicacions en transport, producció, finances i computació.Un gran número de procesos de toma de decisiones en sectores estratégicos como el transporte y la producción representan problemas NP-difíciles. Frecuentemente, estos problemas se caracterizan por altos niveles de incertidumbre y dinamismo. Las metaheurísticas son métodos populares para resolver problemas difíciles de optimización de manera rápida. Sin embargo, suelen asumir que los inputs, las funciones objetivo y las restricciones son deterministas y se conocen de antemano. Estas fuertes suposiciones conducen a trabajar con problemas simplificados. Como consecuencia, las soluciones obtenidas pueden tener un pobre rendimiento. Las simheurísticas integran simulación en metaheurísticas para resolver problemas estocásticos de una manera natural. De manera similar, las learnheurísticas combinan aprendizaje estadístico y metaheurísticas para abordar problemas en entornos dinámicos, donde los inputs pueden depender de la estructura de la solución. En este contexto, las principales aportaciones de esta tesis son: el diseño de las learnheurísticas, una clasificación de trabajos que combinan estadística / aprendizaje automático y metaheurísticas, y varias aplicaciones en transporte, producción, finanzas y computación.A large number of decision-making processes in strategic sectors such as transport and production involve NP-hard problems, which are frequently characterized by high levels of uncertainty and dynamism. Metaheuristics have become the predominant method for solving challenging optimization problems in reasonable computing times. However, they frequently assume that inputs, objective functions and constraints are deterministic and known in advance. These strong assumptions lead to work on oversimplified problems, and the solutions may demonstrate poor performance when implemented. Simheuristics, in turn, integrate simulation into metaheuristics as a way to naturally solve stochastic problems, and, in a similar fashion, learnheuristics combine statistical learning and metaheuristics to tackle problems in dynamic environments, where inputs may depend on the structure of the solution. The main contributions of this thesis include (i) a design for learnheuristics; (ii) a classification of works that hybridize statistical and machine learning and metaheuristics; and (iii) several applications for the fields of transport, production, finance and computing

Tool for discovering sequential patterns in financial markets

The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality

Data mining in manufacturing: a review based on the kind of knowledge

In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques

Capturing Risk in Capital Budgeting

NPS NRP Technical ReportThis proposed research has the goal of proposing novel, reusable, extensible, adaptable, and comprehensive advanced analytical process and Integrated Risk Management to help the (DOD) with risk-based capital budgeting, Monte Carlo risk-simulation, predictive analytics, and stochastic optimization of acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The research covers topics of traditional capital budgeting methodologies used in industry, including the market, cost, and income approaches, and explains how some of these traditional methods can be applied in the DOD by using DOD-centric non-economic, logistic, readiness, capabilities, and requirements variables. Stochastic portfolio optimization with dynamic simulations and investment efficient frontiers will be run for the purposes of selecting the best combination of programs and capabilities is also addressed, as are other alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. The results include actionable intelligence developed from an analytically robust case study that senior leadership at the DOD may utilize to make optimal decisions. The main deliverables will be a detailed written research report and presentation brief on the approach of capturing risk and uncertainty in capital budgeting analysis. The report will detail the proposed methodology and applications, as well as a summary case study and examples of how the methodology can be applied.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injur