Network planning is an essential phase in successfully operating state-of-the-art telecommunication systems. It helps carriers increase revenues by deploying the right technologies in a cost effective manner. More importantly, through the network planning phase, carriers determine the capital needed to build the network as well as the competitive pricing for the offered services. Through this phase, radio tower locations are selected from a pool of candidate locations so as to maximize the net revenue acquired from servicing a number of subscribers. In the Universal Mobile Telecommunication System (UMTS) which is based on the Wideband Code Division Multiple Access scheme (W-CDMA), the coverage area of each tower, called a cell, is not only affected by the signal's attenuation but is also affected by the assignment of the users to the towers. As the number of users in the system increases, interference levels increase and cell sizes decrease. This complicates the network planning problem since the capacity and coverage problems cannot be solved separately. To identify the optimal base station locations, traffic intensity and potential locations are determined in advance, then locations of base stations are chosen so as to satisfy minimum geographical coverage and minimum quality of service levels imposed by licensing agencies. This is implemented through two types of power control mechanisms. The power based power control mechanism, which is often discussed in literature, controls the power of the transmitted signal so that the power at the receiver exceeds a given threshold. On the other hand, the signal-to-interference ratio (SIR) based power control mechanism controls the power of the transmitted signal so that the ratio of the power of the received signal over the power of the interfering signals exceeds a given threshold. Solving the SIR based UMTS/W-CDMA network planning problem helps network providers in designing efficient and cost effective network infrastructure. In contrast to the power based UMTS/W-CDMA network planning problem, the solution of the SIR based model results in higher profits. In SIR based models, the power of the transmitted signals is decreased which lowers the interference and therefore increases the capacity of the overall network. Even though the SIR based power control mechanism is more efficient than the power based power control mechanism, it has a more complex implementation which has gained less attention in the network planning literature. In this thesis, a non-linear mixed integer problem that models the SIR based power control system is presented. The non-linear constraints are reformulated using linear expressions and the problem is exactly solved using a Benders decomposition approach. To overcome the computational difficulties faced by Benders decomposition, two novel extensions are presented. The first extension uses the analytic center cutting plane method for the Benders master problem, in an attempt to reduce the number of times the integer Benders master problem is solved. Additionally, we describe a heuristic that uses the analytic center properties to find feasible solutions for mixed integer problems. The second extension introduces a combinatorial Benders decomposition algorithm. This algorithm may be used for solving mixed integer problems with binary variables. In contrast to the classical Benders decomposition algorithm where the master problem is a mixed integer problem and the subproblem is a linear problem, this algorithm decomposes the problem into a mixed integer master problem and a mixed integer subproblem. The subproblem is then decomposed using classical Benders decomposition, leading to a nested Benders algorithm. Valid cuts are generated at the classical Benders subproblem and are added to the combinatorial Benders master problem to enhance the performance of the algorithm. It was found that valid cuts generated using the analytic center cutting plane method reduce the number of times the integer Benders master problem is solved and therefore reduce the computational time. It was also found that the combinatorial Benders reduces the complexity of the integer master problem by reducing the number of integer variables in it. The valid cuts generated within the nested Benders algorithm proved to be beneficial in reducing the number of times the combinatorial Benders master problem is solved and in reducing the computational time that the overall algorithm takes. Over 110 instances of the UMTS/W-CDMA network planning problem ranging from 20 demand points and 10 base stations to 140 demand points and 30 base stations are solved to optimality.

In this study, the seat inventory control problem is considered for airline networks from the perspective of a risk-averse decision maker. In the revenue management literature, it is generally assumed that the decision makers are risk-neutral. Therefore, the expected revenue is maximized without taking the variability or any other risk factor into account. On the other hand, risk-sensitive approach provides us with more information about the behavior of the revenue. The risk measure we consider in this study is the probability that revenue is less than a predetermined threshold level. In the risk-neutral cases, while the expected revenue is maximized, the probability of revenue being less than such a predetermined level might be high. We propose three mathematical models to incorporate the risk measure under consideration. The optimal allocations obtained by these models are numerically evaluated in simulation studies for example problems. Expected revenue, coefficient of variation, load factor and probability of the poor performance are the performance measures in the simulation studies. According to the results of these simulations, it shown that the proposed models can decrease the variability of the revenue considerably. In other words, the probability of revenue being less than the threshold level is decreased. Moreover, expected revenue can be increased in some scenarios by using the proposed models. The approach considered in this thesis is especially proposed for small scale airlines because risk of obtaining revenue less than the threshold level is more for this type of airlines as compared to large scale airlines.

An important and challenging problem that Process Engineers frequently encounter is the determination of appropriate control structures that minimize the loss of process performance under the effect of uncertainties. This can be achieved by selecting subsets of controlled and manipulated variables and designing their interconnection (controller synthesis). This is known as the Control Structure Selection Problem (CSSP) In this Thesis, a systematic optimization methodology, based on the back-off concept proposed by Prof J. D. Perkins and co-workers, is presented for the CSSP. The proposed formulation offers the following improvements: a) improves the accuracy of calculations and b) reduces computational time and effort. Specifically, the error involved in the approximation of the nonlinear constraint that defines the magnitude of the back-off vector (needed for control structure selection) is reduced by the introduction of a more accurate linear approximation. In addition, the methodology is able to track the effect of simultaneously occurring disturbances at the same time and estimate their worst impact on process economics. The reduction of computational time is achieved by eliminating the state variables from the final formulation. In this way, the number of equations needed for the CSSP solution is significantly reduced and allows the algorithm to locate the solution faster without affecting the performance. The proposed methodology is firstly applied in a classical distillation column (medium scale) and in a complex and highly nonlinear reactive distillation column (large scale). The results obtained from these case studies made the way for the application of the methodology on the plantwide problem of the benchmark Vinyl Acetate monomer production plant in order to demonstrate the benefits of the proposed algorithm. / Η παρούσα εργασία παρουσιάζει μια συστηματική μεθοδολογία για την εύρεση βέλτιστων δομών ρύθμισης σε συστήματα μεγάλης κλίμακας, όπως για παράδειγμα ολοκληρωμένες μονάδες παραγωγής και βασίζεται στην ελαχιστοποίηση των επιπτώσεων των διαταραχών στην οικονομική απόδοση μιας διεργασίας. Το κύριο στοιχείο της μεθοδολογίας είναι το διάνυσμα υποχώρησης από τους ενεργούς περιορισμούς (μ), το οποίο προτάθηκε από τον Prof. J.D. Perkins και την ερευνητική του ομάδα. Η προτεινόμενη μεθοδολογία ενσωματώνει τα κύρια χαρακτηριστικά της μεθοδολογίας του διανύσματος (μ) και παρουσιάζει μια σειρά βελτιώσεων με στόχο τον περιορισμό των μειονεκτημάτων που απέτρεπαν την εφαρμογή της σε συστήματα μεγάλης κλίμακας. Οι βελτιώσεις επικεντρώνονται σε δύο ζητήματα: α) αύξηση της ακρίβειας των υπολογισμών και β) μείωση του υπολογιστικού φόρτου και χρόνου. Η αύξηση της ακρίβειας των υπολογισμών εντοπίζεται στην κατασκευή ενός βελτιωμένου προσεγγιστικού προβλήματος για την κατασκευή κάτω φραγμάτων για τη βέλτιστη λύση. Η βασική ιδέα πίσω από τη προτεινόμενη βελτίωση βασίζεται στη προσέγγιση των μη γραμμικών όρων που εμφανίζονται με ένα σύνολο γραμμικών εξισώσεων. Επίσης για πιο ακριβείς υπολογισμούς, εξετάζεται κάθε διαταραχή ξεχωριστά σε ένα εύρος συχνοτήτων και στη συνέχεια η μέγιστη επίδραση της καθεμίας χρησιμοποιείται από τον αλγόριθμο έτσι ώστε να υπολογιστεί η μέγιστη δυνατή επίπτωση τους στην οικονομική απόδοση της διεργασίας Η μείωση του υπολογιστικού φόρτου και χρόνου επιτυγχάνεται μέσω της απαλοιφής των μεταβλητών κατάστασης. Με αυτό τον τρόπο, ο αριθμός των εξισώσεων που απαιτείται για την επίλυση του προβλήματος μειώνεται σημαντικά και εντοπίζει τη βέλτιστη λύση σε μικρότερο αριθμό επαναλήψεων της μεθόδου, γεγονός που επιτρέπει την εφαρμογή της σε προβλήματα μεγάλης κλίμακας. Τέλος, η προτεινόμενη μεθοδολογία έχει εφαρμοστεί σε δύο αποστακτικές στήλες και τα αποτελέσματα άνοιξαν το δρόμο για την εφαρμογή της μεθόδου σε μια μονάδα παραγωγής οξικού μεθυλεστέρα, όπου τα πλεονεκτήματα της μεθόδου είναι περισσότερο ορατά και πρακτικά χρήσιμα.

Ο τραπεζικός τομέας υφίσταται σημαντικές αλλαγές τα τελευταία χρόνια σε διεθνές επίπεδο, ως απόρροια των αλλαγών στο γενικότερο οικονομικό γίγνεσθαι. Ειδικότερα στη χώρα μας είναι έκδηλη τα τελευταία χρόνια η ανάγκη για αναπροσαρμογή του τρόπου λειτουργίας των πιστωτικών ιδρυμάτων, ώστε να προσαρμοστούν στις μεταβαλλόμενες απαιτήσεις της πελατειακής τους βάσης. Στόχος της παρούσας εργασίας είναι να προσεγγιστεί το ζήτημα της αναδιάρθρωσης των τραπεζικών δικτύων, όπως αυτά έχουν προκύψει μετά από εξαγορές ή συγχωνεύσεις, με απώτερο στόχο την βέλτιστη εξυπηρέτηση των πελατών με το μικρότερο δυνατό κόστος λειτουργίας. Για να επιτευχθεί η αναδιάρθρωση προτείνονται δύο μαθηματικά μοντέλα χωροθέτησης εγκαταστάσεων, που εξετάζουν το πρόβλημα με βάση δύο διαφορετικούς άξονες: το ένα στοχεύοντας στην ελαχιστοποίηση του κόστους και το δεύτερο στην μεγιστοποίηση της καλυπτόμενης ζήτησης με δεδομένο προϋπολογισμό. Για την επίλυση των μαθηματικών μοντέλων αξιοποιήθηκαν δεδομένα μεγάλου τραπεζικού ομίλου που δραστηριοποιείται στην Ελλάδα, επικεντρώνοντας στο υπάρχον εγκατεστημένο δίκτυο εντός του Δήμου Πατρέων. Από την εμπειρική εφαρμογή διαπιστώθηκε σαφής πλεονασμός του υπάρχοντος δικτύου σε μονάδες και προσωπικό, ενώ παράλληλα τα μοντέλα καταλήγουν σε διαφορετικές λύσεις χωροθέτησης για κάθε εκδοχή του προβλήματος. Με όποιο τρόπο όμως και να προσεγγιστεί το πρόβλημα της αναδιάρθρωσης, φαίνεται ότι τα αποτελέσματα αναφορικά με το πλήθος των μονάδων και του απασχολούμενου προσωπικού συγκλίνουν, εξασφαλίζοντας ταυτόχρονα σημαντική μείωση του κόστους λειτουργίας. / The banking sector is undergoing significant changes recently at an international level, as a consequence of changes in the general economic status. Especially in our country, the need for adjusting the operation of credit institutions to adapt to the changing demands of their customer base is obvious. The aim of this paper is to approach the issue of restructuring of banking networks, as they have arisen after mergers or acquisitions, aiming to optimal customer service at the lowest possible operating cost. To achieve the restructuring we propose two mathematical models of facility location, considering the problem on two different axes: firstly aiming at minimizing the cost and secondly at maximizing the demand covered with pre-given budget. To solve the mathematical models we utilized data from a large banking group operating in Greece, focusing on existing established network within the Municipality of Patras. The empirical application showed a clear redundancy of the present network units and personnel, while models result in different solutions of facility location for each version of the problem. Whichever way used to approach the problem of restructuring, it seems that the results regarding the number of units and personnel converge, while ensuring a significant reduction in operating costs.

Disertaciniame darbe, pasitelkus deformuojamo kūno mechanikos energinius principus ir matematinio programavimo teoriją, iš vieningų pozicijų išnagrinėtos tiek tamprių, tiek tamprių-plastinių sistemų deformacijų darnos (Sen-Venano) lygtys. Sprendžiant energinio principo apie papildomos energijos minimumą pagrindu sudarytą ekstremumo analizės uždavinį, įrodoma, kad yra tik trys nepriklausomos Sen-Venano lygtys su atitinkamai performuotomis kraštinėmis sąlygomis. Prisitaikomumo teorija nagrinėja tamprių-plastinių konstrukcijų, veikiamų kintamos-kartotinės apkrovos, būvį, pasitelkdama tiek tamprumo, tiek plastiškumo teorijų pagrindines lygtis ir priklausomybes: disertaciniame darbe pavyko, pasinaudojant Kuno ir Takerio optimalumo sąlygomis, metodiškai pagrįstai įjungti į plastinį konstrukcijų skaičiavimą liekamųjų deformacijų darnos lygtis. Taigi, disertacijoje Kuno ir Takerio sąlygos originaliai pritaikytos tamprumo teorijos lygtims įtempiais ir asociatyvinio tekėjimo dėsnio išraiškoms plastiškumo teorijoje gauti. Pasinaudojant gautaisiais rezultatais patobulinta prisitaikančių lenkiamų plokščių optimizavimo teorija ir sukurti nauji tokių uždavinių sprendimo metodai. Netiesinių uždavinių matematiniai modeliai, sudaryti taikant pusiausvirų baigtinių elementų metodą, sprendžiami iteraciniu būdu, pasitelkus Rozeno projektuojamųjų gradientų algoritmą. Darbui būdinga tai, kad matematinio programavimo teorija optimizavimo problemos nagrinėjimą lydi nuo matematinio modelio sudarymo iki... [toliau žr. visą tekstą] / Adapted perfectly elastic-plastic structure satisfies strength conditions and it is safe with respect to cyclic-plastic collapse. But it can do not satisfy its serviceability requirements, for instance, stiffness ones. Therefore, not only strength, but also stiffness conditions-constraints should be included in the discrete mathematical models of bending plate parameter or load variation bound optimization problems (exactly such problems are considered in the dissertation). Using mathematical programming not only new optimization technique of bending plates at shakedown is developed, but also relation between Kuhn-Tucker conditions and strain compatibility (Saint-Venant) equations and dependences of associative yield law of the deformable body mechanics is showed in the dissertation. Mathematical models of nonlinear problems are constructed applying method of equilibrium elements and are solved by iterations using Rosen project gradient algorithm. The feature of this research work is that the theory of mathematical programming accompanies investigation of optimization problem from the construction of the mathematical model up to its numerical solution, at the same time revealing mechanical meaning optimality criterion of applied Rosen algorithm.

Optimization problems (to which is dedicated this dissertation) of structural mechanics are introductory stage of structure optimum design based on principles of solid deformable body mechanics, mathematical programming theory, its methods and their mechanical interpretation. In order to base calculation on real operating conditions of structure, it is necessary evaluate as exact as possible structure material properties, external effects and other factors in mathematical models of optimization problems. Partially it is achieved by including plastic properties of material. Calculation and design of the structures, taking in to account plastic strains, allows to use their bearing capacity more efficiently and make more economic project (in this dissertation research is developed on the basis of perfect plasticity theory). From the other side, real effect for structure are often cyclic (variable repeated load character is also evaluated in this work). In the dissertation it is assumed that load is quasi–static and is characterised by load variation bounds (deterministic formulation of problems is considered). Under repeated loading a structure can lose its serviceability because of its progressive plastic failure or because of alternating strain. But, if residual forces together with variable part that do not violate the admissible bounds appear in the initial stage of loading, the structure adapts to existing load and further behaves elastically. This phenomenon is... [to full text]

This dissertation investigated farm management concerns faced by grain producers due to the acquisition of various precision agriculture technologies. The technologies evaluated in the three manuscripts included 1) auto-steer navigation, 2) automatic section control, and 3) autonomous machinery. Each manuscript utilized a multifaceted economic model in a whole-farm decision-making framework to determine the impact of precision agriculture technology on machinery management, production management, and risk management. This approach allowed for a thorough investigation into various precision agriculture technologies which helped address the relative dearth of economic studies of precision agriculture and farm management. Moreover, the research conducted on the above technologies provided a wide array of economic insight and information for researchers and developers to aid in the advancement of precision agriculture technologies. Such information included the risk management potential of auto-steer navigation and automatic section control, and the impact the technologies had on optimal production strategies. This dissertation was also able to provided information to guide engineers in the development of autonomous machinery by identifying critical characteristics and isolating the most influential operating machine. The inferences from this dissertation intend to be employed in an extension setting with the purpose of educating grain producers on the impacts of implementing such technologies.

Distribution system voltage and VAR control (VVC) is a technique that combines conservation voltage reduction and reactive power compensation to operate a distribution system at its optimal conditions. Coordinated VVC can provide major economic benefits for distribution utilities. Incorporating distributed generation (DG) to VVC can improve the system efficiency and reliability. The first part of this dissertation introduces a direct optimization formulation for VVC with DG. The control is formulated as a mixed integer non-linear programming (MINLP) problem. The formulation is based on a three-phase power flow with accurate component models. The VVC problem is solved with a state of the art open-source academic solver utilizing an outer approximation algorithm. Applying the approach to several test feeders, including IEEE 13-node and 37-node radial test feeders, with variable load demand and DG generation, validates the proposed control. Incorporating renewable energy can provide major benefits for efficient operation of the distribution systems. However, when the number of renewables increases the system control becomes more complex. Renewable resources, particularly wind and solar, are often highly intermittent. The varying power output can cause significant fluctuations in feeder voltages. Traditional feeder controls are often too slow to react to these fast fluctuations. DG units providing reactive power compensation they can be utilized in supplying voltage support when fluctuations in generation occur. The second part of this dissertation focuses on two new approaches for dual-layer VVC. In these approaches the VVC is divided into two control layers, slow and fast. The slow control obtains optimal voltage profile and set points for the distribution control. The fast control layer is utilized to maintain the optimal voltage profile when the generation or loading suddenly changes. The MINLP based VVC formulation is utilized as the slow control. Both local reactive power control of DG and coordinated quadratic programming (QP) based reactive power control is considered as the fast control approaches. The effectiveness of these approaches is studied with test feeders, utility load data, and fast-varying solar irradiance data. The simulation results indicate that both methods achieve good results for VVC with DG.

Backgounding beef cattle is an inherently risky venture. Producers faceproduction risks as well as marketing risks. If a backgrounding operation is to be viable,these risks should be addressed and effectively managed. While some effective riskmanagement tools are currently available to livestock producers, some other potentiallyuseful risk management tools, for various reasons, have been previously unavailable.Two such tools which could help livestock producers achieve the overall goal ofmanaging net income risk are a program for managing feed ingredient nutrient and pricevariability in the selection of minimum cost feed rations and government subsidizedlivestock price insurance.Due to lack of data and limited computational power of solvers, risk has seldombeen introduced into the feed ration selection process. Presently, both feed ingredientnutritional data and appropriate solvers are available, allowing for risk to be fullyconsidered in this decision-making process. Only recently has there been policy effortsto establish subsidized price or revenue insurance for livestock producers. Theintroduction of such insurance to livestock producers offers potential risk managementbenefit but also has the potential to introduce improper incentives to livestock producers.This study will evaluate both of the aforementioned livestock risk managementtools. In addition to evaluating their effectiveness, the policy concerns of subsidizedlivestock insurance will also be addressed. Results will be relevant to a broad range ofentities. In addition to livestock producers wishing to manage the risks associated withtheir operations, agribusinesses that provide service to these producers such as feed salesor financial lending will benefit from knowing how these risk management strategiesperform. Furthermore, policy makers who will structure livestock insurance products canhopefully do so more efficiently based on the results of the livestock insurance analysis.

This thesis examines the economic and environmental impacts that precision agriculture technologies (PATs) can have on the carbon footprint of a grain farm. An analysis is offered using two manuscripts. The first examines the impacts of three PATs and compares the findings to a conventional farming method. It was found that all three PATs investigated showed a potential Pareto improvement over conventional farming. The second manuscript expanded the model used previously to in order to develop a process to construct a carbon efficient frontier (CEF). The model employed examined uniform and variable rate technologies. In addition to the CEF, a marginal abatement cost curve was constructed. Using these curves in a complementary fashion, more accurate information on the adaptive behavior of farmer technology adoption can be gleaned. the information gleaned for the two manuscripts can give both producers and policy makers the analytical tools needed to make more information decisions with regard to economic and environmental feasibility of PATs.