Two-Stage Stochastic Optimization. An Application in the Third Sector

[en] It is known that most of the problems applied in the real life present uncertainty. In the rst part of the dissertation, basic concepts and properties of the Stochastic Programming have been introduced to the reader, also known as Optimization under Uncertainty. Moreover, since stochastic programs are complex to compute, we have presented some other models such as wait-and-wee, expected value and the expected result of using expected value. The expected value of perfect information and the value of stochastic solution measures quantify how worthy the Stochastic Programming is, with respect to the other models. In the second part, it has been designed and implemented with the modeller GAMS and the optimizer CPLEX an application that optimizes the distribution of non-perishable products, guaranteeing some nutritional requirements with minimum cost. It has been developed within Hazia project, managed by Sortarazi association and associated with Food Bank of Biscay and Basic Social Services of several districts of Biscay.

Constraints to the efficacy of risk management process in entrepreneurial companies

This paper highlights potential factors that affect the degree of efficacy of a formal risk management framework in entrepreneurial organisations. The understanding of entrepreneur’s self-schemas, entrepreneurial organisational culture and working environment is crucial to evaluate the efficacy of a risk management process. This research pointed out two main issues: i) the entrepreneurial decision making process with presence of biases and heuristics in judgement under uncertainty; and ii) the entrepreneurial organisational context that might create constraints to the implementation of a risk management framework.

Maxmin with multiple tastes and beliefs

Tese (doutorado)—Universidade de Brasília, Departamento de Economia, Brasília, 2016.

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.

La disrupción: el punto de partida de la resiliencia o del fracaso empresarial (reflexiones desde la ingeniería)

La perdurabilidad empresarial ha sido un tema recurrente en la literatura sobre dirección de empresas. A pesar de los avances, la liquidación de las empresas aumenta permanentemente. Buscando alternativas de mejora se estudia el caso de dos empresas cuadragenarias dedicadas a prestar servicios de consultoría en ingeniería eléctrica y civil que, en condiciones de crisis, implementaron acciones que les permitieron, no sólo mantenerse en el mercado sino también fortalecer su estructura financiera. Los resultados demostraron que un enfoque equilibrado caracterizado por la toma oportuna de decisiones y la definición e implementación de estrategias de negocio efectivas constituyen herramientas óptimas para asegurar un mayor grado de resiliencia empresarial.

la influencia de la felicidad en las decisiones de inversión de activos de largo plazo para una muestra de siete gerentes financieros en la ciudad de Bogotá en el año 2016.

El presente artículo contribuye con la investigación de las Finanzas Corporativas del Comportamiento, rama de las finanzas corporativas que considera que el individuo que toma decisiones financieras no es completamente racional y que por hecho existen sesgos psicológicos que influyen en sus decisiones. Este documento se enfoca, desde el punto de vista conceptual y también mediante el análisis de un estudio de campo, en la influencia de la felicidad en las decisiones de inversión en activos de largo plazo para un grupo de siete gerentes ubicados en la ciudad de Bogotá en el año 2016. En el documento se abarca el concepto general de las finanzas corporativas del comportamiento, se define la felicidad y se presentan sub-variables determinantes para la felicidad del individuo como lo son: salud, balance vida/trabajo, educación y habilidades, conexiones sociales y medio ambiente. Finalmente se presenta cómo éstas afectan a los gerentes financieros en sus decisiones de acuerdo a la investigación realizada.

Essays in Vertical Agreements and Consumer Behavior

This thesis collects three independent essays and a literature review. Two of them relate to vertical agreements. The first essay explores a retailer's choice in allocating control rights over the decision of retail prices. Results show that retailers adopt a hybrid configuration as a middle ground between two extremes, where pricing decisions are delegated, for all products, either to retailer or manufacturers. The second essay investigates the make-it-or-license-it choice of a brand owner under the risk of moral hazard when licensing the extension product to a third party. Brand licensing emerges as an equilibrium choice under brand dilution (respectively, enhancement) when the consumer perceives a large (small) distance between the extension product and parent brand. The third essay explores the issue of rating bubbles within online feedback systems by means of a field experiment. The analysis found the presence of positive social influence bias, in that high ratings affect the individual rating behavior in a significant way. The last paper is accompanied by a thorough and deep review of the literature about the consequences of online user ratings on product sales/performance (economic dimension) and product adoption/rating behavior (behavioral dimension). The topic is increasingly investigated by academic researchers and industry professionals alike. This overview presents established results and insights as issues for future research.

The Efficient Use of Multiple Sources of a Nonrenewable Resource under Supply Cost Uncertainty

Uncertainties as to future supply costs of nonrenewable natural resources, such as oil and gas, raise the issue of the choice of supply sources. In a perfectly deterministic world, an efficient use of multiple sources of supply requires that any given market exhausts the supply it can draw from a low cost source before moving on to a higher cost one; supply sources should be exploited in strict sequence of increasing marginal cost, with a high cost source being left untouched as long as a less costly source is available. We find that this may not be the efficient thing to do in a stochastic world. We show that there exist conditions under which it can be efficient to use a risky supply source in order to conserve a cheaper non risky source. The benefit of doing this comes from the fact that it leaves open the possibility of using it instead of the risky source in the event the latter’s future cost conditions suddenly deteriorate. There are also conditions under which it will be efficient to use a more costly non risky source while a less costly risky source is still available. The reason is that this conserves the less costly risky source in order to use it in the event of a possible future drop in its cost.

Uncertainty in the estimation of potential evapotranspiration under climate change.

21st century climate change is projected to result in an intensification of the global hydrological cycle, but there is substantial uncertainty in how this will impact freshwater availability. A relatively overlooked aspect of this uncertainty pertains to how different methods of estimating potential evapotranspiration (PET) respond to changing climate. Here we investigate the global response of six different PET methods to a 2 °C rise in global mean temperature. All methods suggest an increase in PET associated with a warming climate. However, differences in PET climate change signal of over 100% are found between methods. Analysis of a precipitation/PET aridity index and regional water surplus indicates that for certain regions and GCMs, choice of PET method can actually determine the direction of projections of future water resources. As such, method dependence of the PET climate change signal is an important source of uncertainty in projections of future freshwater availability.

A flexible consensus scheme for multicriteria group decision making under linguistic assessments

The present paper proposes a flexible consensus scheme for group decision making, which allows one to obtain a consistent collective opinion, from information provided by each expert in terms of multigranular fuzzy estimates. It is based on a linguistic hierarchical model with multigranular sets of linguistic terms, and the choice of the most suitable set is a prerogative of each expert. From the human viewpoint, using such model is advantageous, since it permits each expert to utilize linguistic terms that reflect more adequately the level of uncertainty intrinsic to his evaluation. From the operational viewpoint, the advantage of using such model lies in the fact that it allows one to express the linguistic information in a unique domain, without losses of information, during the discussion process. The proposed consensus scheme supposes that the moderator can interfere in the discussion process in different ways. The intervention can be a request to any expert to update his opinion or can be the adjustment of the weight of each expert`s opinion. An optimal adjustment can be achieved through the execution of an optimization procedure that searches for the weights that maximize a corresponding soft consensus index. In order to demonstrate the usefulness of the presented consensus scheme, a technique for multicriteria analysis, based on fuzzy preference relation modeling, is utilized for solving a hypothetical enterprise strategy planning problem, generated with the use of the Balanced Scorecard methodology. (C) 2009 Elsevier Inc. All rights reserved.

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.