Browsing by Author "Toppila, Antti"
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- Implementation of an algorithm for verifying the non-negativity of a multilinear function in a hypercube
Perustieteiden korkeakoulu | Bachelor's thesis(2014-04-14) Losoi, Henri - Optimal Risk Reduction Portfolios in Fault Tree Analysis
Perustieteiden korkeakoulu | Bachelor's thesis(2013-09-30) Losoi, Markus - A Resource Allocation Model for Standardisation Activities in a Telecommunication Company
Helsinki University of Technology | Master's thesis(2009) Toppila, AnttiCompatibility, interoperability, market growth and technology utilisation are key issues in competitiveness for a telecommunications company. Standardisation can help to achieve these goals. Participation in standardisation is a strategic decision because of long term impacts and commitment to substantially different evolvement paths, and should therefore be linked with company core competencies and believed market growth. However, it is difficult to identify the standardisation activities that improve most the competitive status of the company, because of intangible benefits, uncertainties, large number of alternatives, strategically considerations, etc., which inspire application of decision analysis. This Thesis presents a portfolio model that was developed for a major telecommunications company to support the allocation of resources to standardisation activities. The model assumes that standardisation improves the success rate for pursuing widely adopted technologies, which in turn creates sales. The probabilities for standardisation and widely adopted technology success are altered by reallocating resources, which changes the expected sales from a widely adopted technology. Because the activities are linked (e.g. standardisation and development budgets and synergies/cannibalisation), they are considered as a portfolio when searching the optimal resource allocation. Robustness to parameter estimation errors is achieved by expressing sales as plausible sales intervals. If the realisation of the sales parameter would be known in beforehand they would result in an optimal resource allocation. Therefore the share of resource allocations that are optimal with some sales within the intervals and allocate a specific amount of resources for an activity is used to indicate how good that allocation is for that activity over the plausible sales intervals. If a particular allocation is (never) optima with all values for sales, then it is certain to (never) recommend that allocation. Weaker results indicate an activity as a net gainer or net loser when reallocating resources. The model was applied in an exercise for the telecommunications company involving about a hundred standardisation activities with interactions, and personnel from different parts of the company organisation. The analysis indicated three activities to terminate and suggested that some activities could significantly benefit from having more resources to standardisation, development or both, whereas other were not as sensitive to increased/decreased resources. - Robust reliability and resource allocation - Models and algorithms
School of Science | Doctoral dissertation (article-based)(2016) Toppila, AnttiOrganizational decision makers (DMs) such as companies, institutions and public sector agencies rely on mathematical models for decision support. Often these models have parameters such as probabilities of events and outcomes of actions, which typically are epistemically uncertain due to the lack of historical data or other information. In such cases, DMs often need to understand how this epistemic uncertainty impacts the decision recommendations. This Dissertation considers models for supporting allocation decisions in settings where epistemic uncertainty is modeled explicitly through incomplete information. The resulting decision recommendations that account for epistemic uncertainty are derived through dominance: Alternative A dominates alternative B if A is at least as good as B for all parameters that are compatible with the available incomplete information, and moreover, strictly better for some. A dominated alternative should not be selected, because there exist at least one alternative that is not worse for any parameters and is strictly better for some. Thus, the decision recommendation to select an alternative that is non-dominated (ND) is robust with respect to the epistemic uncertainty. In the models considered in this Dissertation, generating the ND alternatives leads to a computationally challenging combinatorial optimization problem. Several exact algorithms and approximative methods for computing the ND alternatives are developed. The exact methods are based on classical dynamic programming and branch-and-bound algorithms, as well as binary decision diagrams, which have recently been used in solving challenging optimization problems. The simplification methods, on the other hand, are more ad hoc in nature and based on problem specific approaches. This Dissertation contributes by providing ways for analyzing the impact of epistemic uncertainty with incomplete information in application areas which are central in the fields of risk analysis and decision analysis, namely (i) probabilistic risk analysis based on importance measures, (ii) allocation of resources to reliability enhancing actions, (iii) project portfolio selection, and (iv) resource allocation to standardization activities. The developed methods are generic in that they could likely be adopted with small refinements even in other application areas. - Yhteisviat ja intervallitodennäköisyydet vikapuuanalyysissa
Perustieteiden korkeakoulu | Bachelor's thesis(2013-01-17) Jussila, Tomi