Browsing by Subject "Nonlinear programming"

Now showing 1 - 7 of 7

Open Access
Comparison of the formulations for a hub-and-spoke network design problem under congestion
(Elsevier, 2016) Kian, Ramer; Kargar, Kamyar
In this paper, we study the hub location problem with a power-law congestion cost and propose an exact solution approach. We formulate this problem in a conic quadratic form and use a strengthening method which rests on valid inequalities of perspective cuts in mixed integer nonlinear programming. In a numerical study, we compare two well known types of mathematical modeling in the hub-location problems which are solved with different branch and cut strategies. The strength and weakness of the formulations are summarized based on an extensive numerical study over the CAB data set. © 2016 Elsevier Ltd
Open Access
Coordination of staffing and pricing decisions in a service firm
(John Wiley & Sons, 2008) Serel, D. A.; Erel, E.
Customer demand is sensitive to the price paid for the service in many service environments. Using queueing theory framework, we develop profit maximization models for jointly determining the price and the staffing level in a service company. The models include constraints on the average waiting time and the blocking probability. We show convexity of the single-variable subproblem under certain plausible assumptions on the demand and staffing cost functions. Using numerical examples, we investigate the sensitivity of the price and the staffing level to changes in the marginal service cost and the user-specified constraint on the congestion measure.
Open Access
An evaluative study of operation grouping policies in an FMS
(Kluwer Academic Publishers, 2003) Sabuncuoǧlu, İ.; Lahmar, M.
The increased use of flexible manufacturing systems to provide customers with diversified products efficiently has created a significant set of operational challenges for managers. This technology poses a number of decision problems that need to be solved by researchers and practitioners. In the literature, there have been a number of attempts to solve design and operational problems. Special attention has been given to machine loading problems, which involve the assignment of job operations and allocation of tools and resources to optimize specific measures of productivity. Most existing studies focus on modeling the problem and developing heuristics in order to optimize certain performance metrics rather than on understanding the problem and the interaction between the different factors in the system. The objective of this paper is to study the machine loading problem. More specifically, we compare operation aggregation and disaggregation policies in a random flexible manufacturing system (FMS) and analyze its interaction with other factors such as routing flexibility, sequencing flexibility, machine load, buffer capacity, and alternative processing-time ratio. For this purpose, a simulation study is conducted and the results are analyzed by statistical methods. The analysis of results highlights the important factors and their levels that could yield near-optimal system performance.
Open Access
Huber approximation for the non-linear ℓ1 problem
(Elsevier, 2006) Pınar, Mustafa Ç.; Hartmann, W. M.
The smooth Huber approximation to the non-linear ℓ1 problem was proposed by Tishler and Zang (1982), and further developed in Yang (1995). In the present paper, we use the ideas of Gould (1989) to give a new algorithm with rate of convergence results for the smooth Huber approximation. Results of computational tests are reported.
Open Access
A Kuznets curve in environmental efficiency: an application on OECD countries
(Springer Netherlands, 2000) Zaim, O.; Taskin, F.
The role of the environment is an important issue in policy making and the accurate assessment of the environmental conditions is vital. In this paper, using nonparametric techniques, an environmental efficiency index is developed for each of the OECD countries. These indexes allow one both to do cross section comparisons on the state of each country's production process in its treatment of undesirable outputs and also to trace each country's modification of their production processes overtime. Furthermore in this study we investigate the factors underlying societies' environmental concerns that eventually lead to changes in the environmental efficiency. The results provide further empirical evidence for the environmental Kuznets curve hypothesis.The role of the environment is an important issue in policy making and the accurate assessment of the environmental conditions is vital. In this paper, using nonparametric techniques, an environmental efficiency index is developed for each of the OECD countries. These indexes allow one both to do cross section comparisons on the state of each country's production process in its treatment of undesirable outputs and also to trace each country's modification of their production processes overtime. Furthermore in this study we investigate the factors underlying societies' environmental concerns that eventually lead to changes in the environmental efficiency. The results provide further empirical evidence for the environmental Kuznets curve hypothesis.An environmental efficiency index for each OECD state is developed, using nonparametric techniques. The indices facilitate cross-section comparisons on the status of each nation's production processes in its treatment of waste and pollutants. Modifications of production processes over time can also be tracked. Factors underlying societal environmental concerns that eventually result in changes in environmental efficiency are also analyzed, and results provide additional empirical evidence for the environmental Kuznets curve hypothesis.
Open Access
Scaling forecasting algorithms using clustered modeling
(Association for Computing Machinery, 2015) Gür, İ.; Güvercin, M.; Ferhatosmanoglu, H.
Research on forecasting has traditionally focused on building more accurate statistical models for a given time series. The models are mostly applied to limited data due to efficiency and scalability problems. However, many enterprise applications require scalable forecasting on large number of data series. For example, telecommunication companies need to forecast each of their customers’ traffic load to understand their usage behavior and to tailor targeted campaigns. Forecasting models are typically applied on aggregate data to estimate the total traffic volume for revenue estimation and resource planning. However, they cannot be easily applied to each user individually as building accurate models for large number of users would be time consuming. The problem is exacerbated when the forecasting process is continuous and the models need to be updated periodically. This paper addresses the problem of building and updating forecasting models continuously for multiple data series. We propose dynamic clustered modeling for forecasting by utilizing representative models as an analogy to cluster centers. We apply the models to each individual series through iterative nonlinear optimization. We develop two approaches: The Integrated Clustered Modeling integrates clustering and modeling simultaneously, and the Sequential Clustered Modeling applies them sequentially. Our findings indicate that modeling an individual’s behavior using its segment can be more scalable and accurate than the individual model itself. The grouped models avoid overfits and capture common motifs even on noisy data. Experimental results from a telco CRM application show the method is efficient and scalable, and also more accurate than having separate individual models.
Open Access
Trajectory control of a quadrotor using a control allocation approach
(IEEE, 2017) Zaki, H.; Ünel, M.; Yıldız, Yıldıray
A quadrotor is an underactuated unmanned aerial vehicle with four inputs to control the dynamics. Trajectory control of a quadrotor is a challenging task and usually tackled in a hierarchical framework where desired/reference attitude angles are analytically determined from the desired command signals, i.e. virtual controls, that control the positional dynamics of the quadrotor and the desired yaw angle is set to some constant value. Although this method is relatively straightforward, it may produce large and nonsmooth reference angles which must be saturated and low-pass filtered. In this work, we show that the determination of desired attitude angles from virtual controls can be viewed as a control allocation problem and it can be solved numerically using nonlinear optimization where certain magnitude and rate constraints can be imposed on the desired attitude angles and the yaw angle need not be constant. Simulation results for both analytical and numerical methods have been presented and compared. Results for constrained optimization show that the flight performance is quite satisfactory.