Browsing by Subject "Uncertainty"

Now showing 1 - 20 of 26

Open Access
Chapter 22: Futures and options
(Edward Elgar Publishing, 2023-05-18) Gürkaynak, Refet S.; Wright, Jonathan H.
We survey the history, market structure, pricing and usage of futures and options contracts. We focus in particular on their ability to provide high-frequency measures of expectations, uncertainty, higher moments, and investor risk aversion. Futures and options are a rich and growing treasure trove of information to academics and policymakers alike.
Open Access
Concepts and analysis in facility location under uncertainty : applications to 1-median problem
(2001-08) Demir, Muhittin Hakan
Open Access
Contextual learning for unit commitment with renewable energy sources
(IEEE, 2017) Lee, H. -S.; Tekin, Cem; Schaar, M.; Lee, J. -W.
In this paper, we study a unit commitment (UC) problem minimizing operating costs of the power system with renewable energy sources. We develop a contextual learning algorithm for UC (CLUC) which learns which UC schedule to choose based on the context information such as past load demand and weather condition. CLUC does not require any prior knowledge on the uncertainties such as the load demand and the renewable power outputs, and learns them over time using the context information. We characterize the performance of CLUC analytically, and prove its optimality in terms of the long-term average cost. Through the simulation results, we show the performance of CLUC and the effectiveness of utilizing the context information in the UC problem.
Open Access
Decision-making in complex environments: a study of women entrepreneurs in Pakistan
(2023-12) Younus, Iqra
This thesis examines Pakistani women's entrepreneurial experiences, emphasizing on their unique challenges and decision-making processes. It explores the context of Pakistan's complex sociocultural, political, and economic environment and how these factors interact closely to shape their entrepreneurial journeys. The main focus of this research is to study and analyze how these women navigate uncertainty and challenges while making business decisions. A purposive sampling technique and a qualitative methodology is employed in this study - basing the research on the actual experiences of 36 Pakistani women entrepreneurs. It demonstrates how they deal with and adjust to difficulties brought on by the economic challenges of the country, such as market volatility and currency instability. The study also emphasizes the significance of socio-cultural norms, particularly those pertaining to gender roles, which both impede and motivate them. The research reveals that despite these challenges, Pakistani women entrepreneurs display determination and adaptability. They balance external guidance and their own judgment strategically, making decisions using a combination of intuition, heuristics, and rational analysis. It also highlights the importance of elements like personal and family values, emotional intelligence, and faith in business decisions. These women frequently establish firms from home, reflecting cultural constraints and their strategic response to obstacles.
Embargo
Drones for relief logistics under uncertainty after an earthquake
(Elsevier BV, 2023-03-03) Dükkancı, Okan; Koberstein, Achim; Kara, Bahar Y.
This study presents a post-disaster delivery problem called the relief distribution problem using drones under uncertainty, in which critical relief items are distributed to disaster victims gathered at assembly points after a disaster, particularly an earthquake. Because roads may be obstructed by debris after an earthquake, drones can be used as the primary transportation mode. As the impact of an earthquake cannot be easily predicted, the demand and road network uncertainties are considered. Additionally, the objective is to minimize the total unsatisfied demand subject to a time-bound constraint on the deliveries, as well as the range and capacity limitations of drones. A two-stage stochastic programming and its deterministic equivalent problem formulations are presented. The scenario decomposition algorithm is implemented as an exact solution approach. To apply this study to real-life applications, a case study is conducted based on the western (European) side of Istanbul, Turkey. The computational results are used to evaluate the performance of the scenario decomposition algorithm and analyze the value of stochasticity and the expected value of perfect information under different parametric settings. We additionally conduct sensitivity analyses by varying the key parameters of the problem, such as the time-bound and capacities of the drones.
Open Access
Entanglement and its operational measure
(Springer, 2006) Klyachko, Alexander A.; Öztop, Barış; Shumovsky, Alexander S.
An operational representation of concurrence measuring the entanglement of bipartite systems by means of averages of basic observables is discussed. We prove the validity of this representation for bipartite systems with any dimension of a single-party Hilbert space. We show that Wigner-Yanase "skew" information gives a reasonable estimation of the amount of entanglement (in ebits) carried by mixed two-qubit states.
Open Access
Essays on uncertainty
(2015) Karaman, Seçil Yıldırım
This dissertation consists of three essays on the real impacts of uncertainty shocks. The first essay develops a theoretical model to investigate the impact of financial market uncertainty on real economic downturns. The second and third essays empirically investigate the differences in the adverse impact of uncertainty shocks on real output for countries with different financial development levels and central bank characteristics. The first essay investigates whether financial market volatility induces real downturns in a dynamic stochastic general equilibrium framework with heterogenous agents. In the model, an increase in the volatility of future stock price expectations of nonsophisticated agents causes an increase in the volatility of stock prices. In response to the increase in stock price volatility, the model generates reduction in consumption, investment, employment and output. The model contributes to the literature by modeling financial market volatility in a general equilibrium framework, highlighting the mechanisms through which the impact works, and providing estimates of its magnitude. The second essay investigates whether financial development moderates the negative impact of uncertainty shocks on real economic activity. To test this conjecture, I compare the impact of macro level uncertainty as measured by stock market volatility on real GDP growth for countries with different financial development levels. To address potential endogeneity concerns, the estimation is made using Two Stage Least Squares technique where plausibly exogenous disaster shocks are used as instruments for stock market volatility. The estimation results based on a panel data set of 54 countries between 1971 and 2009 are consistent with the conjecture that uncertainty shocks hurt countries with developed financial markets less. The third essay investigates the role of institutional characteristics of the central banks in moderating the negative consequences of uncertainty shocks using the same identification strategy as the second essay. The results provide strong evidence that central bank independence reduces the adverse effects of uncertainty shocks. As for the impact of central bank transparency, while in some specifications the results support its mitigating impact on the adverse effect of uncertanity, in others it doesn’t have a significant moderating impact. In the light of the restrictions on the transparency data set which spans 44 countries between 1998 and 2009, more comprehensive studies may be needed to reach a stronger verdict for its impact.
Open Access
Expected Scott-Suppes utility representation
(Academic Press, 2018) Dalkıran, Nuh Aygün; Dokumacı, O. E.; Kara, Tarık
We provide an axiomatic characterization for an expected Scott-Suppes utility representation. Such a characterization is the natural analog of the von Neumann-Morgenstern expected utility theorem for semiorders and it is noted as an open problem by Fishburn (1968). Expected Scott-Suppes utility representation is analytically tractable and can be used in applications that study preferences with intransitive indifference under uncertainty. Our representation offers a decision-theoretical interpretation for epsilon equilibrium as well.
Open Access
Fair allocation of in-kind donations in post-disaster phase
(2024-05) Varol, Zehranaz
Disaster response aims to address the immediate needs of the affected populations quickly in highly uncertain circumstances. In disaster relief supply chains, the demand comes from disaster victims (typically considered as internally dis-placed populations), while the supply mostly consists of in-kind donations. This dissertation focuses on finding a fair mechanism to distribute a scarce relief item among a set of demand points under supply uncertainty. Primary concerns, restrictive elements, and unknown parameters change throughout the response phase, which substantially affects the structure of the underlying problems. Thus, the first part of this study provides a temporal classification of disaster response (e.g., into subphases) based on evolving features of demand and supply. As the next step, a donation management problem is structured considering the characteristics of a selected subphase. We first focus on the deterministic donation management problem, which is formulated as a multi-criteria multi-period location-inventory problem with service distance constraints. A set of mobile facilities, called points of distribution (PoDs), is used to distribute the collected supply. In particular, two decisions are made for every period of the planning horizon: (i) where to locate a limited number of mobile PoDs and (ii) what quantity to deliver to each demand node from each PoD. We consider three criteria. The first two involve the so-called deprivation cost, which measures a population’s “suffering” due to a shortage. The third objective is related to the total travel time. Two resulting vectorial optimization models are solved using the ε-constraint method, and the corresponding Pareto frontiers are obtained. Computational results are presented that result from applying the proposed methodological developments to an instance of the problem using real data as well as a generated one. Finally, the stochastic counterpart of the problem is addressed with the aim of minimizing a deprivation cost-based objective. The uncertain supply parameters are integrated into the model using a multi-stage stochastic programming (MSSP) approach. The MSSP model is tested on a real data set to assess and evaluate possible policies that can be adopted by decision-makers. Two matheuristic approaches are employed to handle the exponential growth of the scenario trees: a rolling horizon algorithm and a scenario tree reduction algorithm. A set of computational experiments is performed to evaluate the performance of the proposed methodologies. Overall, the results show that the proposed algorithms can better support the decision-making process when fairness is of relevance.
Open Access
Five essays on monetary policy applications in an open economy under economic uncertainty and shocks
(2004) Dinçer, Nazire Nergiz
In this dissertation, we analyzed the monetary policy applications under uncertainty and shocks and their effects on the economy. The uncertainties we concern are inflation uncertainty and exchange rate risk, whereas the shocks are the unexpected exchange rate shocks, change in parity and capital flights. The case study is Turkey, except the analysis on inflation uncertainty, which is on G-7 countries. The analyses on inflation uncertainty suggest that inflation increases inflation uncertainty for G-7 countries, whereas inflation uncertainty decreases inflation for four countries. Therefore, when uncertainty is high, the central bank reduces those real costs at the margin by reducing inflation. On the other hand, the effects of exchange rate risk are an increase in prices, a depreciation of the real exchange rate, and a decrease in the output. In the face of unexpected currency depreciation or appreciation, the economic activity decreases. The effects of an improvement in the USD-Euro parity on an open economy, where the denomination composition of trade is asymmetric is an appreciation of the real exchange rate, an increase in the relative income and an improvement in the trade balance. The empirical analyses on capital outflows suggest that growth decreases, inflation increases and exchange rate depreciates, which are critical negative signals for an economy. Overall this dissertation suggests that when designing a policy program, it is important to consider the possible deviations from the policies. Otherwise, it would not be possible to achieve the targets, moreover the costs would be too high for the economy.
Open Access
Hedging production schedules against uncertainty in manufacturing environment with a review of robustness and stability research
(Taylor & Francis, 2009) Sabuncuoglu, I.; Goren, S.
Scheduling is a decision-making process that is concerned with the allocation of limited resources to competing tasks (operations of jobs) over a time period with the goal of optimising one or more objectives. In theory, the objective is usually to optimise some classical system performance measures such as makespan, tardiness/earliness and flowtime under deterministic and static assumptions. In practice, however, scheduling systems operate in dynamic and stochastic environments. Hence, there is a need to incorporate both uncertainty and dynamic elements into the scheduling process. In this paper, the major issues involved in scheduling decisions are discussed and the basic approaches to tackle these problems in manufacturing environments are analysed. Proactive scheduling is then focused on and several robustness and stability measures are presented. Previous research on scheduling robustness and stability is also reviewed and further research directions are suggested.
Open Access
Humanitarian facility location under uncertainty: Critical review and future prospects
(Elsevier, 2021-01-08) Dönmez, Zehranaz; Yetiş Kara, Bahar; Karsu, Özlem; Saldanha-da-Gama, F.
This paper provides a comprehensive review of the research done on facility location problems under uncertainty in a humanitarian context. The major goal is to summarize and help structuring this topic, which has increasingly attracted the attention of the scientific community. The literature is reviewed from different perspectives namely, in terms of the type of facilities involved, the decisions to make, the criteria to optimize, the paradigm used for capturing uncertainty, and the solution method adopted. The detailed analysis provided in the manuscript also contributes to identifying the distinguishing features of the problems in the topic. An outcome of the state-of-the-art presented is the identification of the current research trends, expectations and holes in the existing knowledge thus highlighting relevant research directions.
Open Access
Humanitarian logistics under uncertainty: planning for sheltering and evacuation
(Springer Cham, 2023-05-09) Bayram, V.; Y. Kara, Bahar; Saldanha-da-Gama, F.; Yaman, H.; Eiselt, H. A.; Marianov, V.
This chapter focuses on a major area emerging in the context of humanitarian logistics: emergency evacuation planning and management. Two major aspects are covered: shelter site location and evacuation traffic assignment. Both are discussed separately before an integrated problem is considered. Throughout the chapter, uncertainty in the underlying parameters is assumed. The major sources of uncertainty analyzed are the demand for sheltering and capacity of the edges in the underlying network. Congestion issues emerge in this context that are also considered. Different paradigms for capturing uncertainty are considered for illustrative purposes, namely, robust optimization, chance-constrained programming, and stochastic programming.
Open Access
The impact of uncertainty on investment : overview
(2009) Yılmaz, Erdal
Common consensus in the real option literature is that there is a negative relationship between uncertainty and investment. One of the explanations can be stated that the increased in uncertainty leads to move up the value of waiting and consequently has an adverse effect on investment. Contrary to the existing theory, Sarkar (2000) and Gryglewicz et all (2006) find that this negative relationship is not always correct. The former paper demonstrates that an increase in uncertainty can actually hasten the probability of making an investment under certain condition (when project life is short and level of uncertainty is low) and hence uncertainty has a positive effect on investment. Result of the latter paper is exceptional in the sense that uncertainty may accelerate irreversible investment without building on the convexity of the marginal product of capital. In this thesis, we compare these two papers and investigate whether they support each other or not in the framework of real option theory. Moreover, we made some numerical simulations in order to understand clearly impact of other variables on investment along with uncertainty.
Open Access
Is Roger Federer more loss averse than Serena Williams?
(Routledge, 2017) Anbarci, N.; Arin, K. P.; Okten, C.; Zenker, C.
Using data from the high-stakes 2013 Dubai professional tennis tournament, we find that, compared with a tied score, (i) male players have a higher serve speed and thus exhibit more effort when behind in score, and their serve speeds get less sensitive to losses or gains when score difference gets too large, and (ii) female players do not change their serve speed when behind, while serving slower when ahead. Thus, male players comply more with Prospect Theory exhibiting more loss aversion and reflection effect. Our results are robust to controlling for player fixed effects and characteristics with player random effects. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Restricted
Knowledge, uncertainty, and behavior
(1985) Wilde, Keith D.
Open Access
Long short-term memory for improved transients in neural network adaptive control
(IEEE, 2023-07-03) İnanç, Emirhan; Gürses, Yiğit; Habboush, Abdullah; Yıldız, Yıldıray
In this study, we propose a novel adaptive control architecture, which provides dramatically better performance compared to conventional methods. What makes this architecture unique is the synergistic employment of a traditional, Adaptive Neural Network (ANN) controller and a Long Short-Term Memory (LSTM) network. LSTM structures, unlike the standard feed-forward neural networks, take advantage of the dependencies in an input sequence, which helps predict the evolution of an uncertainty. Through a training method we introduced, the LSTM network learns to compensate for the deficiencies of the ANN controller. This substantially improves the transient response by allowing the controller to quickly react to unexpected events. Through careful simulation studies, we demonstrate that this architecture can improve the estimation accuracy on a diverse set of unseen uncertainties. We also provide an analysis of the contributions of the ANN controller and LSTM network, identifying their individual roles in compensating low and high frequency error dynamics. This analysis provides insight into why and how the LSTM augmentation improves the system’s transient response.
Open Access
Markov decision process formulations for management of pumped hydro energy storage systems
(2023-06) Toufani, Parinaz
Renewable energy sources have received much attention to mitigate the high dependence on fossil fuels and the resulting environmental impacts. Since the variability and intermittency of such renewable sources lower the reliability and security of energy systems, they should often be accompanied by efficient and flexible storage units. This dissertation focuses on pumped hydro energy storage (PHES) facilities, which are one of the most commonly used large-scale storage technologies. We study the energy generation and storage problem for PHES facilities with two connected reservoirs, where water is pumped from the lower reservoir to the upper reservoir to store energy during low-demand/low-electricity price periods, and released back to the lower reservoir to generate energy during high-demand/high-electricity price periods. The first part of this dissertation investigates the potential benefits of transforming conventional cascading hydropower stations into PHES facilities by replacing turbines with reversible ones. The second part compares the short-term cash flows obtained from different PHES configurations (cascading vs. non-cascading facilities, upstream vs. downstream inflows, and closed-loop facilities). We formulate both problems as Markov decision processes under uncertainty in the streamflow rate and electricity price. We include the streamflow rate and electricity price as exogenous state variables in our formulation. We analytically derive bounds on the profit improvement obtained from PHES transformation in the first part and bounds on the revenue differences obtained from different configurations in the second part. In the last part, we establish several structural properties of the optimal profit function for general two-reservoir PHES systems. We show the optimality of a state-dependent threshold policy for non-cascading PHES facilities when the electricity price is always positive. Leveraging our structural results, we construct a heuristic solution method for more general settings when the electricity price can also be negative. In this dissertation, we also conduct comprehensive numerical experiments with data-calibrated time series models to provide insights into the optimal operation of PHES facilities, considering distinct seasons with different streamflow rates, different negative electricity price occurrence frequencies, and different system parameters.
Embargo
Optimization of pumped hydro energy storage systems under uncertainty: A review
(Elsevier, 2023-12-20) Toufani, P.; Karakoyun, E. Ç.; Nadar, Emre; Fasso, O. B.; Kocaman, Ayşe Selin
This paper provides an overview of the research dealing with optimization of pumped hydro energy storage (PHES) systems under uncertainty. This overview can potentially stimulate the scientific community’s interest and facilitate future research on this topic. We review the literature from various perspectives, including the optimization problem type, objective function, physical characteristics of the PHES facility, paradigm used to capture uncertainty, and solution method adopted. We then identify several research gaps and future research directions for energy researchers. This review highlights the need for developing optimization models such as Markov decision processes that can represent uncertainties in renewable energy sources and electricity markets more accurately, constructing multi-objective models that consider not only economic but also environmental impacts, investigating underrepresented solar-PHES systems and PHES sizing problems, addressing nonlinear characteristics of PHES facilities, and optimizing bidding strategies in sequential or coordinated electricity markets.
Open Access
Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment
(John Wiley & Sons, 2012) Goren, S.; Sabuncuoglu, I.; Koc, U.
The ability to cope with uncertainty in dynamic scheduling environments is becoming an increasingly important issue. In such environments, any disruption in the production schedule will translate into a disturbance of the plans for several external activities as well. Hence, from a practical point of view, deviations between the planned and realized schedules are to be avoided as much as possible. The term stability refers to this concern. We propose a proactive approach to generate efficient and stable schedules for a job shop subject to processing time variability and random machine breakdowns. In our approach, efficiency is measured by the makespan, and the stability measure is the sum of the variances of the realized completion times. Because the calculation of the original measure is mathematically intractable, we develop a surrogate stability measure. The version of the problem with the surrogate stability measure is proven to be NP-hard, even without machine breakdowns; a branch-and-bound algorithm is developed for this problem variant. A tabu search algorithm is proposed to handle larger instances of the problem with machine breakdowns. The results of extensive computational experiments indicate that the proposed algorithms are quite promising in performance.