Browsing by Subject "Decision making"

Now showing 1 - 20 of 60

Open Access
Activity recognition invariant to sensor orientation with wearable motion sensors
(MDPI AG, 2017) Yurtman, A.; Barshan, B.
Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
Open Access
Adaptive game-theoretic decision making for autonomous vehicle control at roundabouts
(Institute of Electrical and Electronics Engineers Inc., 2019) Tian, R.; Li, S.; Li, N.; Kolmanovsky, İ.; Girard, A.; Yıldız, Yıldıray; Teel, A. R.; Egerstedt, M.
In this paper, we propose a decision making algorithm for autonomous vehicle control at a roundabout intersection. The algorithm is based on a game-theoretic model representing the interactions between the ego vehicle and an opponent vehicle, and adapts to an online estimated driver type of the opponent vehicle. Simulation results are reported.
Open Access
Age-based vs. stock level control policies for a perishable inventory system
(2001) Tekin, E.; Gürler Ü.; Berk, E.
In this study, we investigate the impact of modified lotsize-reorder control policy for perishables which bases replenishment decisions on both the inventory level and the remaining lifetimes of items in stock. We derive the expressions for the key operating characteristics of a lost sales perishable inventory model, operating under the proposed age-based policy, and examine the sensitivity of the optimal policy parameters with respect to various system parameters. We compare the performance of the suggested policy to that of the classical (Q,r) type policy through a numerical study over a wide range of system parameters. Our findings indicate that the age-based policy is superior to the stock level policy for slow moving perishable inventory systems with high service levels.
Open Access
An algorithm based on facial decomposition for finding the efficient set in multiple objective linear programming
(Elsevier, 1996) Sayın, S.
We propose a method for finding the efficient set of a multiple objective linear program based on the well-known facial decomposition of the efficient set. The method incorporates a simple linear programming test that identifies efficient faces while employing a top-down search strategy which avoids enumeration of efficient extreme points and locates the maximally efficient faces of the feasible region. We suggest that discrete representations of the efficient faces could be obtained and presented to the Decision Maker. Results of computational experiments are reported.
Open Access
Analysis of a decentralized supply chain under partial cooperation
(2005) Güllü, R.; Van Houtum G. J.; Sargut F. Z.; Erkip, N.
In this article, we analyze a decentralized supply chain consisting of a supplier and two independent retailers. In each order cycle, retailers place their orders at the supplier to minimize inventory-related expected costs at the end of their respective response times. There are two types of lead times involved. At the end of the supplier lead time, retailers are given an opportunity to readjust their initial orders (without changing the total order size), so that both retailers can improve their expected costs at the end of respective retailer lead times (the time it takes for items to be shipped from the supplier to the retailers). Because of the possibility of cooperation at the end of supplier lead time, each retailer will consider the other's order-up-to level in making the ordering decision. Under mild conditions, we prove the existence of a unique Nash equilibrium for the retailer order-up-to levels, and show that they can be obtained by solving a set of newsboy-like equations. We also present computational analysis that provides valuable managerial insight for design and operation of decentralized systems under the possibility of partial cooperation.
Open Access
Analyzing impact of experience curve on ROI in the software product line adoption process
(Elsevier BV, 2015) Tüzün, E.; Tekinerdogan, B.
Context Experience curve is a well-known concept in management and education science, which explains the phenomenon of increased worker efficiency with repetitive production of a good or service. Objective We aim to analyze the impact of the experience curve effect on the Return on Investment (ROI) in the software product line engineering (SPLE) process. Method We first present the results of a systematic literature review (SLR) to explicitly depict the studies that have considered the impact of experience curve effect on software development in general. Subsequently, based on the results of the SLR, the experience curve effect models in the literature, and the SPLE cost models, we define an approach for extending the cost models with the experience curve effect. Finally, we discuss the application of the refined cost models in a real industrial context. Results The SLR resulted in 15 primary studies which confirm the impact of experience curve effect on software development in general but the experience curve effect in the adoption of SPLE got less attention. The analytical discussion of the cost models and the application of the refined SPLE cost models in the industrial context showed a clear impact of the experience curve effect on the time-to-market, cost of development and ROI in the SPLE adoption process. Conclusions The proposed analysis with the newly defined cost models for SPLE adoption provides a more precise analysis tool for the management, and as such helps to support a better decision making.
Open Access
Approaches for inequity-averse sorting
(Elsevier, 2016) Karsu, Ö.
In this paper we consider multi-criteria sorting problems where the decision maker (DM) has equity concerns. In such problems each alternative represents an allocation of an outcome (e.g. income, service level, health outputs) over multiple indistinguishable entities. We propose three sorting algorithms that are different from the ones in the current literature in the sense that they apply to cases where the DM's preference relation satisfies anonymity and convexity properties. The first two algorithms are based on additive utility function assumption and the third one is based on the symmetric Choquet integral concept. We illustrate their use by sorting countries into groups based on their income distributions using real-life data. To the best of our knowledge our work is the first attempt to solve sorting problems in a symmetric setting.
Open Access
Aviation risk perception: a comparison between experts and novices
(Wiley-Blackwell Publishing, 2004) Thomson, M. E.; Önkal D.; Avcioǧlu, A.; Goodwin, P.
This article describes an exploratory investigation of the risk perceptions of experts and novices in relation to helicopter operations, under conditions where the participants are matched on various characteristics previously found to affect perceptions, such as demographic, gender, and background factors. The study reports considerable evidence of perceptual differences between the two participant groups (i.e., expert pilots and candidate pilots). We find that the experts' perceptions of relative risks are more veridical, in terms of their higher correlation with the true relative frequencies. A significant positive correlation between the flight hours and the contextual risk-taking tendency is also shown, leading the experienced pilots' choices toward risky alternatives in scenarios - a potential result of their overconfidence based on superior task performance. Possible explanations are offered for the findings and potential avenues for future research are identified.
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Bant genişliği kısıtı altında videonun en iyi iletimi
(IEEE, 2006-04) Gürses, E.; Akar, G. B.; Akar, Nail
In this paper, we propose an optimal video streaming framework using retransmissions based on the theory of Markov Decision Processes (MDP). Using MDPs, we calculate average reward optimal policies so as to maximize the on time delivery probability of video frames in the transmission window while conforming to network-imposed available bandwidth constraints. The effectiveness of the proposed approach is validated by comparing the results with theoretically obtained rate-distortion curves corresponding to the optimal policies by using the distortion model in [2] © 2006 IEEE.
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Benefit-cost analysis in state and local investment decisions
(1979) David, Elizabeth
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Classifying human leg motions with uniaxial piezoelectric gyroscopes
(2009) Tunçel O.; Altun, K.; Barshan, B.
This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted from the raw inertial sensor data in different ways, are used in the classification process. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, least-squares method (LSM), k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). A performance comparison of these classification techniques is provided in terms of their correct differentiation rates, confusion matrices, computational cost, and training and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that BDM, in general, results in the highest correct classification rate with relatively small computational cost. © 2009 by the authors.
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Compromising system and user interests in shelter location and evacuation planning
(Elsevier Ltd, 2015) Bayram V.; Tansel, B.T.; Yaman H.
Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority's point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the importance of the number and locations of shelter sites and the trade-off between efficiency and fairness. © 2014 Elsevier Ltd.
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Computer vision based method for real-time fire and flame detection
(Elsevier BV, 2006-01-01) Töreyin, B. U.; Dedeoǧlu, Y.; Güdükbay, Uğur; Çetin, A. Enis
This paper proposes a novel method to detect fire and/or flames in real-time by processing the video data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame and fire flicker is detected by analyzing the video in the wavelet domain. Quasi-periodic behavior in flame boundaries is detected by performing temporal wavelet transform. Color variations in flame regions are detected by computing the spatial wavelet transform of moving fire-colored regions. Another clue used in the fire detection algorithm is the irregularity of the boundary of the fire-colored region. All of the above clues are combined to reach a final decision. Experimental results show that the proposed method is very successful in detecting fire and/or flames. In addition, it drastically reduces the false alarms issued to ordinary fire-colored moving objects as compared to the methods using only motion and color clues. © 2005 Elsevier B.V. All rights reserved.
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Diffusion of geograpgic information system at municipalities in Istanbul
(Chamber of Mining Engineers of Turkey, 2015-04) Çavur, M.; Özturan, M.; Karaduman, C.; İçli, Abdullah Bera
This study aims to develop a better understanding of diffusion of Geographic Information Systems within municipalities and examines the infrastructure of Istanbul municipalities and whether they are ready for this technology or not. This study uses two research methods: The first one comprises interviews with the experts of GIS in Turkey. The second one comprises questionnaires conducted with Geographic Information Systems - related departments of Istanbul municipalities. Data collected online have been analyzed by using descriptive statistics, reliability tests, Anova and regression to test the hypotheses. One of the findings is that almost half of the municipalities implement Geographic Information Systems without a vision or a plan for the future. Another finding is that Geographic Information Systems is mainly used to perform registration and maintenance functions instead of supporting the decision-making process. Finally, there is an optimistic expectation of municipalities regarding the use of Geographic Information Systems in the future.
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Dynamic lot sizing and tool management in automated manufacturing systems
(Elsevier, 2002) Aktürk, M. S.; Önen, S.
The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters.
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Evaluating predictive performance of judgemental extrapolations from simulated currency series
(Elsevier, 1999) Pollock, A. C.; Macaulay, A.; Önkal-Atay, D.; Wilkie-Thomson, M. E.
Judgemental forecasting of exchange rates is critical for financial decision-making. Detailed investigations of the potential effects of time-series characteristics on judgemental currency forecasts demand the use of simulated series where the form of the signal and probability distribution of noise are known. The accuracy measures Mean Absolute Error (MAE) and Mean Squared Error (MSE) are frequently applied quantities in assessing judgemental predictive performance on actual exchange rate data. This paper illustrates that, in applying these measures to simulated series with Normally distributed noise, it may be desirable to use their expected values after standardising the noise variance. A method of calculating the expected values for the MAE and MSE is set out, and an application to financial experts' judgemental currency forecasts is presented.
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Examining leaders' orientations to structural constraints: Turkey's 1991 and 2003 Iraq war decisions
(Palgrave Macmillan Ltd., 2017) Cuhadar E.; Kaarbo, J.; Kesgin, B.; Taner, B. O.
Explanations of states' security decisions prioritise structural - systemic, institutional and cultural - constraints that characterise foreign security decisions as a function of external/international, domestic/institutional, or normative/cultural factors. By examining Turkey's 1990-1991 and 2003 Iraq war decisions systematically, we problematise this prioritisation of structure, and we investigate the dynamic relationship between structural constraints and leaders in their decision-making environments. In these cases, while the structural constraints remain constant or indeterminate, the decision outcomes and the decision-making process differ significantly. Our findings, based on structured-focused comparison, process tracing, and leadership trait analysis, suggest that the leaders' personalities and how they react to constraints account for this difference and that dependence on only one set of factors leads to an incomplete understanding of security policies and international politics. We contribute to the broader understanding of leaders' personalities by suggesting that self-confidence and cognitive complexity are the key traits distinguishing leaders' orientations towards structural constraints. © 2016 Macmillan Publishers Ltd.
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Examining proactive strategic decision-making flexibility in new product development
(Wiley-Blackwell Publishing, 2012) Kandemir, D.; Acur, N.
While strategic flexibility is widely accepted as a prerequisite for a firm's success, its application in strategic decision making to a firm's new product development (NPD) activities is limited to only a few studies. Furthermore, many organizations still have difficulties creating proactive strategic flexibility in their decision-making processes. Past research studies have largely ignored the relationship between strategic decision-making flexibility and firms' resources and/or capabilities and success in the context of NPD. This study advances strategic flexibility by adopting the proactive approach of NPD decision-making flexibility and by examining its role in translating organizational resources and capabilities into NPD success. This study draws upon the resources, capabilities (i.e., flexibility), and performance framework to show how proactive strategic decision-making flexibility plays a crucial role in developing new products that can create new opportunities and comply with market needs. Therefore, this research aims to (1) develop an operational definition of strategic decision-making flexibility and (2) propose a framework to understand the drivers and the subsequent new product performance outcomes of strategic decision-making flexibility. This study adopts the proactive perspective of strategic decision-making flexibility and defines it as a capability that enables firms to develop NPD strategies to respond to future changes in the environment. The analysis, based on data collected from 103 European firms, shows that that the effects of long-term orientation, strategic planning, internal commitment, and innovative climate on proactive strategic decision-making flexibility are significant. The findings indicate specifically the roles of both champions and gatekeepers, who infuse a firm's knowledge with a clear understanding of its resources, constraints, and market needs, thereby enhancing decision makers' motivation to behave proactively to precipitate transformation. The results also reveal a positive association between proactive strategic decision-making flexibility and NPD performance outcomes. As such, strategic flexibility provides firms with an ability to adapt to changing environments and to create new market opportunities, product, and technological arenas, and to deliver successful new products. When firms open new market, technological, and product arenas, they can easily foresee their new demands and changes and successfully deliver new products, meeting customer needs/demands, and offering benefits such as quality, cost, and timeliness. This study therefore provides a valuable reference point for future research in strategic decision-making flexibility in NPD.
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Functional contour-following via haptic perception and reinforcement learning
(Institute of Electrical and Electronics Engineers, 2018) Hellman, R. B.; Tekin, Cem; Schaar, M. V.; Santos, V. J.
Many tasks involve the fine manipulation of objects despite limited visual feedback. In such scenarios, tactile and proprioceptive feedback can be leveraged for task completion. We present an approach for real-time haptic perception and decision-making for a haptics-driven, functional contour-following task: The closure of a ziplock bag. This task is challenging for robots because the bag is deformable, transparent, and visually occluded by artificial fingertip sensors that are also compliant. A deep neural net classifier was trained to estimate the state of a zipper within a robot's pinch grasp. A Contextual Multi-Armed Bandit (C-MAB) reinforcement learning algorithm was implemented to maximize cumulative rewards by balancing exploration versus exploitation of the state-action space. The C-MAB learner outperformed a benchmark Q-learner by more efficiently exploring the state-action space while learning a hard-to-code task. The learned C-MAB policy was tested with novel ziplock bag scenarios and contours (wire, rope). Importantly, this work contributes to the development of reinforcement learning approaches that account for limited resources such as hardware life and researcher time. As robots are used to perform complex, physically interactive tasks in unstructured or unmodeled environments, it becomes important to develop methods that enable efficient and effective learning with physical testbeds.
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A game theoretical model of traffic with multiple interacting drivers for use in autonomous vehicle development
(IEEE, 2016) Oyler, D. W.; Yıldız, Yıldıray; Girard, A. R.; Li, N. I.; Kolmanovsky, İ. V.
This paper describes a game theoretical model of traffic where multiple drivers interact with each other. The model is developed using hierarchical reasoning, a game theoretical model of human behavior, and reinforcement learning. It is assumed that the drivers can observe only a partial state of the traffic they are in and therefore although the environment satisfies the Markov property, it appears as non-Markovian to the drivers. Hence, each driver implicitly has to find a policy, i.e. a mapping from observations to actions, for a Partially Observable Markov Decision Process. In this paper, a computationally tractable solution to this problem is provided by employing hierarchical reasoning together with a suitable reinforcement learning algorithm. Simulation results are reported, which demonstrate that the resulting driver models provide reasonable behavior for the given traffic scenarios.