Portfolio Optimization Using Evolutionary Algorithms

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsPortfolio optimization is a widely studied field in modern finance. It involves finding the optimal balance between two contradictory objectives, the risk and the return. As the number of assets rises, the complexity in portfolios increases considerably, making it a computational challenge. This report explores the application of the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and Genetic Algorithm (GA) in the field of portfolio optimization. MOEA/D and GA have proven to be effective at finding portfolios. However, it remains unclear how they perform when compared to traditional approaches used in finance. To achieve this, a framework for portfolio optimization is proposed, using MOEA/D, and GA separately as optimization algorithms and Capital Asset Pricing Model (CAPM) and Mean-Variance Model as methods to evaluate portfolios. The proposed framework is able to produce weighted portfolios successfully. These generated portfolios were evaluated using a simulation with subsequent (unseen) prices of the assets included in the portfolio. The simulation was compared with well known portfolios in the same market and other market benchmarks (Security Market Line and Market Portfolio). The results obtained in this investigation exceeded expectation by creating portfolios that perform better than the market. CAPM and Mean-Variance Model, although they fail to model all the variables that affect the stock market, provide a simple valuation for assets and portfolios. MOEA/D using Differential Evolution operators and the CAPM model produced the best portfolios in this research. Work can still be done to accommodate more variables that can affect markets and portfolios, such as taxes, investment horizon and costs for transactions

Selecting R&D Projects at BMW: A Case Study of Adopting Mathematical Programming Models

Research and development (R&D) project selection is a critical interface between the product development strategy of an organization and the process of managing projects day-to-day. This article describes the project selection problem faced by an R&D group of BMW (Munich, Germany). The problem was structured as minimizing the gap between target performance of the technology to be developed and actual performance of the current technology along chosen criteria. A mathematical programming model helped this organization to increase the transparency of their selection process, which previously had been based on experience coupled with evaluation of individual projects in isolation Implementation was a success in that the predevelopment group continues to use the model to make better decisions. However, the organization did not use the model for its intended purpose: constrained optimization. The traditional explanation for this partial implementation is that the analytical model did not capture all considerations relevant to optimization (e.g., uncertainty or strategic fit), and that further model refinements are required to achieve further implementation. We offer an alternative explanation, one based on the technology transfer literature. The diffusion of the analytical model from academia to industry faced the same problems as any technology transfer: Significant tacit knowledge had to be transferred along with the codified knowledge of the analytical model. This required iterated problem solving, which required the limited time and resources of the diffusing agents (academia) as well as the adopting agents (industry). Thus, the organization adopted only those elements of the modeling method that could be transferred within the resource constraints, focusing on those elements offering the highest benefit per effort invested

A Multi-Skilled Approach to Property Maintenance Considering Temporal, Spatial and Resource Constraints

With the continued increase in age of the United States housing and building stock, as well as the continued need to maintain properties across the U.S., the need for timely, cost-optimal maintenance is ever more critical. This paper proposes the application of a mathematical model to aid in the scheduling and assignment of construction and maintenance tasks, considering the multi-skilled workforce. The benefit of this approach is to take advantage of the economies of scale that can be developed using cross-functional skilled workers with varying levels of competence and efficiency. This approach schedules and assigns tasks using data from maintenance task software datasets, using the least-cost, competent worker available for the job while also considering the trade-off between skilled labor cost and travel costs, both in terms of travel wage and vehicle wear and tear. The model is enhanced to include pairing between a mentor and an apprentice, where combined efficiency and pairing costs are considered at the same time as travel costs. Due to the practical nature of this research, a case organization was used and data from that firm was analyzed so that operational insights into the necessity of such a model could be considered. The mathematical backbone of the optimization approach to multi-skilled resource allocation considers the temporal and spatial demands of a geographically dispersed property management program. Actual, as opposed to sample, data allows us to evaluate the real financial implications on the case firm, if such an approach to scheduling is used. The generalization of this data provides excellent fit for a model that can be used to assign the best capable worker to the most cost-efficient task, considering deadlines, priorities and availability. Results of this scheduling approach provide significant cost and resource reductions over the historical firm performance, though practical considerations should temper that expectation. The above approach offers exceptional scalability and adaptability with the continued advancement of algorithm approaches to network-distribution and peer-to-peer work platforms

IT portfolio attributes and investment choices

Many Chief Information Officers (CIOs) and senior executives face the challenge of finding the appropriate IT resource allocation to meet enterprise strategic goals across multi-organizational units. To address this problem, my dissertation opens the black box of enterprise strategic IT resource allocation by examining the prioritization and selection of IT investment choices (i.e., IT initiatives). Since IT Portfolio Management (ITPM) involves making applicable decisions to achieve a firm’s strategic objectives by fine-tuning budgeted costs and returns as business conditions change, my dissertation examines an important class of IS decision problems: IT portfolio attributes and investment choices. My research addresses how a firm can systematically profile numerous IT portfolios and provide theoretical insights into the components of the optimal solution. Based on design science, my specialized method incorporates mathematical optimization and computational experiments and combines real-world data using the Monte Carlo approach to simulate the experimental data. Consequently, by combining the suggested IT portfolio attributes while addressing a variety of ITPM-related issues, the main contribution for my research is a new ITPM-related methodology built on three proposed ITPM models/techniques: (1) optimal efficiency across multi-organizational levels/units simultaneously; (2) the most qualified IT portfolio selection that incorporates decision-makers’ risk tolerance levels; and (3) accurately estimating the current financial standing of each project in a portfolio of IT projects over the project’s full lifecycle. By applying the proposed ITPM-related methodology with illustrative examples, I develop theoretical propositions based on my main findings

Tradespace and Affordability – Phase 1

One of the key elements of the SERC’s research strategy is transforming the practice of systems engineering – “SE Transformation.” The Grand Challenge goal for SE Transformation is to transform the DoD community’s current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first, outside-in, document-driven, point-solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise-oriented, hardware-software-human engineered, balanced outside-in and inside-out, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046)

A Longitudinal study of organizational capability development process : rendering project portfolio management capability (PPMC)

This dissertation analyzes the heterogeneous development paths of project portfolio management capability (PPMC). Earlier, modern literature has prioritized its focus on the performance-based classification of organizational capabilities, while their development process remained obscure. Consequently, scholarship advocating high performance organizational capabilities (such as a dynamic capability) are in abundance. However, the evidence of development path-affected performance dissimilarities is rather sparse or otherwise remained implicit due to the increasing conceptual differences among the prominent scholarship. Along with the longitudinal process research design of this research, a critical realism-based retroduction approach has enabled the discovery of the capability investigation framework. This capability dimensions, routines, and performance outcome based framework has been further extended to investigate project portfolio management capability (PPMC). This retroductive framework is operationalized to evidence the nine years of capability development path heterogeneity at three entities of a case company. The research case findings explain the effect of underlying mechanisms, which due to their context dependent outcomes, either positively reinforce the existing development paths or lead to an alternative path selection. The case findings also confirm that higher performance is not universally attributable to any specific organizational capability known in the literature. Instead, the actuation of all three identified learning mechanisms (of a learning organization) can develop high performing organizational capabilities. This research concludes that a capability development process endures through an extemporized mixture of refinement, reconfiguration, and transformation activities. As a result, an organizational capability always remains idiosyncratic in its details and, hence, produce diverse performance outcomes. Finally, this PhD research has created a critical realist model to extend the emergent theory of capability path dependence to the other organizational contexts.Tämä tutkimus analysoi projektiportfolion hallintaa koskevan kyvykkyyden moninaisia kehittämisvaihtoehtoja. Aiempi tutkimus on keskittynyt organisaation toimintaa tukevien kyvykkyyksien luokitteluun, mutta kyvykkyyksien kehittymistä on tutkittu vähemmän. Kyvykkyyden kehittymiseen (kuten dynaamiseen kyvykkyyteen) tähtäävä tutkimus keskittyy enimmäkseen organisaation näkökulmaan. Lisäksi kyvykkyyden kehittymistutkimusta vaikeuttaa se, että alan keskeiset tutkijat käyttävät keskenään erilaista terminologiaa. Tämä tutkimus on pitkittäinen ja siinä rakennettiin kriittisen realismin lähestymistavan avulla kyvykkyyden kehittymisen tutkimista varten viitekehys. Kyvykkyyden osatekijöitä, rutiineja ja toiminnan tuloksia kuvaavaa viitekehystä kehitettiin edelleen niin, että sitä voidaan käyttää organisaation projektisalkun hallinnan kyvyn selvittämiseen. Tämän viitekehyksen avulla osoitettiin tapausyrityksen kolmen yksikön kyvykkyyden kehittymispolku yhdeksän vuoden ajalta. Tapaustutkimuksen tulokset selittävät kyvykkyyden kehittymisen mekanismeja, jotka joko vahvistavat organisaation vallitsevia kehittymispolkuja tai johtavat uuden kehittymispolun valintaan. Tapaustutkimukset myös osoittavat, että tehokas toiminta ei ole kirjallisuudessa mainitun yksittäisen organisaation kyvykkyysosatekijän seurausta. Sen sijaan kaikki tunnistetut oppivan organisaation oppimiskeinot kehittävät tehokkaasti toimivan organisaation kyvykkyyksiä. Tämän tutkimuksen johtopäätös on, että kyvykkyyden kehittymisprosessi muodostuu improvisoiduista hienosäätö-, uudelleenkonfigurointi- ja muokkausvaiheista. Niiden tuloksena organisaation kyvykkyys säilyy aina yksityiskohdissaan omaperäisenä ja siten voi tuottaa vaihtelevia tuloksia. Tämä väitöskirja on luonut kriittiseen realismiin perustuvan mallin, jolla laajennetaan uutta kyvykkyyden kehittymispolkuriippuvuuden teoriaa muihin organisaatiokonteksteihin.fi=vertaisarvioitu|en=peerReviewed

Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications

Assessing Offshore Wind Farm Placements in Norway Is NVE’s current plan optimal – or can we do better?

Over the last decade, offshore wind has received increased attention due to global warming and the increase in energy demand. Therefore, it is of the highest interest to develop more renewable energy production to satisfy the increase in energy consumption and reduce global pollution. Even though Norway has excellent hydropower opportunities and is self-sufficient and a leading prosecutor in this field, developing offshore wind is now a goal. In 2020, the Norwegian government opened for wind farm development in Sørlige Nordsjø II and Utsira Nord. The government is also planning to delegate licenses for around 30 gigawatts of offshore wind by 2040. Luckily enough, as we will see throughout this thesis, the Norwegian wind conditions are outstanding for wind power production. Additionally, the technologies surrounding offshore wind farms have become drastically better, making them both more affordable and effective. This paper aims to explore and perform statistical analyses on potential sites for offshore wind farms in Norway. The thesis will have an “investor perspective” and seek optimal locations to maximise production while minimizing variability and costs. As already mentioned, Sørlige Nordsjø II and Utsira Nord are open for production. We want to use these locations as baselines when researching the other areas to see whether one can outperform them. After selecting our locations through a qualitative analysis, we use the dataset NORA3-WP to explore the maximum power production and create portfolios from the selected locations. Objectively, it is hard to determine whether some locations are better than others, but we have overcome some findings. The interpretation from the results is that the South of Lindesnes is stand-alone best in terms of power production and Sharpe ratio. The portfolio evaluation showed that a combination of all the locations except Utsira Nord creates a minimum varianceand a maximum Sharpe ratio–portfolio. We also provide three scenarios with different weights for locations that would satisfy the government’s goal of producing 120 TWh within 2040. Notably, this thesis is heavily influenced by the “investor perspective”, and the calculations are massively simplified. Further and broader research would be necessary before making any final decisions.nhhma

Metodološki okvir za obogaćivanje upravljanja projektnih portfelja agilnim i lean metodama

Predmet istraživanja su metodike upravljanja projektnim portfeljem i mogućnost njihovog poboljšanja, na temelju obogaćivanja agilnim i lean (vitkim, okretnim) konceptima i metodama. Postojeći modeli i procesi upravljanja projektnim portfeljima koriste tradicionalne principe, procedure, planiranje i metode nadzora. Međutim, iako se radi o području intenzivnih istraživanja, agilno i lean upravljanje je relativno novo područje za koje još uvijek nedostaju odgovarajuće spoznaje i praktični rezultati vezani uz utjecaj agilnog pristupa i metodika na procese upravljanja, rizike i kvalitetu. Istraživanje je potvrdilo da predloženi konceptualni okvir upravljanja, koji proizlazi kao jedan od glavnih znanstvenih doprinosa ovog istraživanja, može poboljšati izvedbu menadžmenta procesa projektnih portfelja te smanjiti rizike izvedbe komponenata portfelja (projekata i programa).The subject of this research is project portfolio governance, and its improvement based on agile and lean methods and concepts. The existing project portfolio frameworks and governance processes use traditional principles, regulation, planning, and control methods. Whilst this is an area of intensive research, the agile and lean governance is a relative new domain, for which a certain cognizance and practical results related to influence of agile approach and methods on governance processes, risks, and quality are missing. This research confirms that the new proposed conceptual governance framework, emerging as one of the main scientific contributions from this research, improves the management of project portfolio processes’ execution and reduces the risks of portfolio components’ (projects and programs) implementation. The expected scientific contribution from this research is foremost methodological in introducing of agile and lean project portfolio governance concepts, methods, and processes, followed by creation of the referent agile process governance framework and its taxonomy, and finally in the evaluation of the possibility for the application of the agile governance framework, with the aim of the portfolio components’ implementation risks reduction

Metodološki okvir za obogaćivanje upravljanja projektnih portfelja agilnim i lean metodama

Predmet istraživanja su metodike upravljanja projektnim portfeljem i mogućnost njihovog poboljšanja, na temelju obogaćivanja agilnim i lean (vitkim, okretnim) konceptima i metodama. Postojeći modeli i procesi upravljanja projektnim portfeljima koriste tradicionalne principe, procedure, planiranje i metode nadzora. Međutim, iako se radi o području intenzivnih istraživanja, agilno i lean upravljanje je relativno novo područje za koje još uvijek nedostaju odgovarajuće spoznaje i praktični rezultati vezani uz utjecaj agilnog pristupa i metodika na procese upravljanja, rizike i kvalitetu. Istraživanje je potvrdilo da predloženi konceptualni okvir upravljanja, koji proizlazi kao jedan od glavnih znanstvenih doprinosa ovog istraživanja, može poboljšati izvedbu menadžmenta procesa projektnih portfelja te smanjiti rizike izvedbe komponenata portfelja (projekata i programa).The subject of this research is project portfolio governance, and its improvement based on agile and lean methods and concepts. The existing project portfolio frameworks and governance processes use traditional principles, regulation, planning, and control methods. Whilst this is an area of intensive research, the agile and lean governance is a relative new domain, for which a certain cognizance and practical results related to influence of agile approach and methods on governance processes, risks, and quality are missing. This research confirms that the new proposed conceptual governance framework, emerging as one of the main scientific contributions from this research, improves the management of project portfolio processes’ execution and reduces the risks of portfolio components’ (projects and programs) implementation. The expected scientific contribution from this research is foremost methodological in introducing of agile and lean project portfolio governance concepts, methods, and processes, followed by creation of the referent agile process governance framework and its taxonomy, and finally in the evaluation of the possibility for the application of the agile governance framework, with the aim of the portfolio components’ implementation risks reduction