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<p>We propose an approximation scheme for single-product periodic-review inventory systems with L-natural-convex structure. We lay out three well-studied inventory models, namely the lost-sales system, the perishable inventory system, and the joint inventory-pricing problem. We approximate the value functions for these models by the class of L-natural-convex quadratic functions, through the technique of linear programming approach to approximate dynamic programming. A series of heuristics are derived based on the quadratic approximation, and their performances are evaluated by comparison with existing heuristics. We present the numerical results and show that our heuristics outperform the benchmarks for majority of cases and scale well with long lead times. In this dissertation we also discuss the alternative strategies we have tried but with unsatisfactory result.</p> / Dissertation

Metamorphism is a technique that mutates the binary code using different obfuscations. It is difficult to write a new metamorphic malware and in general malware writers reuse old malware. To hide detection the malware writers change the obfuscations (syntax) more than the behavior (semantic) of such a new malware. On this assumption and motivation, this thesis presents a new framework named MARD for Metamorphic Malware Analysis and Real-Time Detection. We also introduce a new intermediate language named MAIL (Malware Analysis Intermediate Language). Each MAIL statement is assigned a pattern that can be used to annotate a control flow graph for pattern matching to analyse and detect metamorphic malware. MARD uses MAIL to achieve platform independence, automation and optimizations for metamorphic malware analysis and detection. As part of the new framework, to build a behavioral signature and detect metamorphic malware in real-time, we propose two novel techniques, named ACFG (Annotated Control Flow Graph) and SWOD-CFWeight (Sliding Window of Difference and Control Flow Weight). Unlike other techniques, ACFG provides a faster matching of CFGs, without compromising detection accuracy; it can handle malware with smaller CFGs, and contains more information and hence provides more accuracy than a CFG. SWOD-CFWeight mitigates and addresses key issues in current techniques, related to the change of the frequencies of opcodes, such as the use of different compilers, compiler optimizations, operating systems and obfuscations. The size of SWOD can change, which gives anti-malware tool developers the ability to select appropriate parameter values to further optimize malware detection. CFWeight captures the control flow semantics of a program to an extent that helps detect metamorphic malware in real-time. Experimental evaluation of the two proposed techniques, using an existing dataset, achieved detection rates in the range 94% - 99.6% and false positive rates in the range 0.93% - 12.44%. Compared to ACFG, SWOD-CFWeight significantly improves the detection time, and is suitable to be used where the time for malware detection is more important as in real-time (practical) anti-malware applications. / Graduate / 0984 / alam_shahid@yahoo.com

Magistro baigiamajame analizuoti ir įvertinti pasirinkimai elgsenos finansų kontekste bei požiūris į perteklinio pasirinkimo situacijas. Pirmojoje darbo dalyje pateikiama racionalios ekonominės elgsenos kritika, apžvelgiama elgsenos finansų disciplina kaip alternatyva vyraujančiai paradigmai, apžvelgiamos dažniausiai pasireiškiančios euristikos bei polinkiai. Pristatoma per didelio pasirinkimo problema bei pateikiami susisteminti šios srities tyrimai. Pagrindžiant empirinio tyrimo metodiką, antrojoje darbo dalyje, remiantis užsienio autorių tyrimais, parenkami tikrinami polinkiai bei euristikos, sudaromas klausimynas, atliekamas pilotinis tyrimas, sudaroma tyrimo anketa, vertinamas patikimumas. Trečiojoje dalyje lyginami ir taikant statistinius metodus analizuojami empirinio tyrimo rezultatai, ieškoma reikšmingų sąsajų, pateikiamos įžvalgos, apibendrinami rezultatai ir apžvelgiamos galimos tolimesnių tyrimų kryptys. Galiausiai pateikiamos išvados ir siūlomos būsimų tyrimų kryptys. / Master‘s thesis aims to analyze and evaluate choices in the context of behavioral finance and attitude towards overchoice. In the first part of the thesis, criticism of rational choice theory is provided, behavioral finance is portrayed as an alternative to mainstream finance and the most common heuristics and biases are reviewed. The problem of overchoice is discussed and research in this field is reviewed. In the second part of the thesis, methodology for studying choice in the context of behavioral finance and approach to overchoice is formed: the most probable heuristics and biases are chosen, a pilot questionnaire is composed, a pilot survey is carried our, the pilot questionnaire is updated to obtain the final version, validity of the survey is evaluated. In the third part of the thesis, survey results are analyzed, statistically significant relations are sought, insights are provided, results are summarized and possible directions for future research are outlined.

In this thesis the capacitated vehicle routing problem with time windows (VRPTW) is studied, where the objective is to serve a set of geographically dispersed customers with known demands and predefined time windows at the minimum cost. It is hard to find an optimal solution for the VRPTW even if the problem size is small. Therefore, many heuristic methods are developed to obtain near optimal solutions. In this study a local search algorithm is proposed for solving the VRPTW, which consist of route construction and route improvement phases. Computational experiments are conducted with Solomon (1987)&rsquo / s and Homberger and Gehring (1999)&rsquo / s problem sets in order to test the performance of the proposed algorithm. From the computational results encouraging results are obtained in terms of solution quality.

This research project assesses the role played by political sophistication in terms of itsimpact on the voters’ resort to cognitive shortcuts, with reference both to the consciousand non-conscious components of voting decisions. The investigation scrutinisesempirically the way both sophisticated and unsophisticated individuals make politicaljudgments when prompted with cognitive cues in three different settings. In each ofthem a specific type of cue impinges on the political judgment of individuals at adifferent level and leads to a specific decisional outcome. The overall findings castdoubts on the virtues of heuristic reasoning as effective remedy for voters who have tofind their bearings in the ballot box, but they also downplay the importance of politicalsophistication when visual or subliminal cues are involved in the decision. / Aquest projecte de recerca avalua el paper exercit per la sofisticació política en termesdel seu impacte sobre el recurs dels votants als atalls cognitius, amb referència tant alscomponents conscients i no conscients de les decisions de vot. La investigació examinaempíricament la manera com ambdós individus sofisticats i no sofisticats fan judicispolítics quan si li estimuli amb senyals cognitives de tres tipus diferents. En cada und'ells un tipus específic de atall incideix en el judici polític dels individus en un nivelldiferent i condueix a un resultat específic de presa de decisions. Els resultats generalsposen en dubte les virtuts del raonament heurístic com a remei eficaç per als votants ques’han d'orientar a les urnes, sinó que també minimitzen la importància de la sofisticaciópolítica, quan senyals visuals o subliminals estan involucrats en la decisió.

This thesis addresses the omission in the literature of how political context influences the performance of informational shortcuts. In line with this research gap, the first article suggests that parliamentarian and party-oriented systems encourage the performance of ideology, party identification and leadership, as their use increases the probability to participate in elections, while the effective number of parties has no impact. The second article focus on Spain and two contextual shortcuts - incumbency and electoral polls-. The findings indicate that peripheral voters has the highest propensity to vote for left wing parties when the polls show that the left party is going to win the elections and it is the challenger in salient elections or the incumbent in a nonsalient election. The third article analyses the Spanish case and the impact of leader evaluations and ideology on vote choice over time. The findings manifest that while ideology becomes more important, the utility of leader evaluation is reduced once the informational context becomes more fruitful and stable. / Esta tesis aborda la omisión en la literatura de cómo el contexto político influye en el funcionamiento de los atajos informativos. En línea con esta limitación en la literatura, el primer artículo examina qué instituciones promueven un mejor funcionamiento de la ideología, la identificación partidista y el liderazgo, midiendo los efectos de su uso en la probabilidad de participar en las elecciones. La evidencia muestra como los sistemas parlamentarios y los sistemas orientados a partidos promueven un mejor funcionamiento de los tres atajos, mientras que el número efectivo de partidos no tiene impacto. El segundo artículo se basa en España y dos atajos contextuales –estar en el gobierno y los sondeos electorales- para explorar el saber convencional de que un mayor porcentaje de voto beneficia a los partidos de izquierdas. La evidencia indica que los votantes periféricos tienen la mayor probabilidad de votar a partidos de izquierdas cuando en elecciones relevantes los sondeos muestran que el partido de izquierdas va a ganar las elecciones y está en la oposición o cuando está en el gobierno en elecciones no importantes. El tercer artículo analiza el caso español y el impacto de las evaluaciones de los líderes y la ideología en el voto a través del tiempo. Los resultados manifiestan que, si bien la ideología se vuelve más importante, la utilidad de la evaluación el líder se reduce una vez que el contexto informativo se vuelve más rico y estable.

Rail track operators have traditionally used manual methods to construct train timetables. Creating a timetable can take several weeks, and so the process usually stops once the first feasible timetable has been found. It is suspected that this timetable is often far from optimal. Existing methods schedule track maintenance once the best train timetable has been determined and allow little or no adjustments to the timetable. This approach almost certainly produces suboptimal integrated solutions since the track maintenance schedule is developed with the imposition of the previously constructed train timetable. The research in this thesis considers operationally feasible methods to produce integrated train timetables and track maintenance schedules so that, when evaluated according to key performance criteria, the overall schedule is the best possible. This research was carried out as part of the Cooperative Research Centre for Railway Engineering and Technologies. We developed a method that uses a local search meta-heuristic called 'problem space search'. A fast dispatch heuristic repeatedly selects and moves a track possessor (train or maintenance task) through the network; this results in a single integrated schedule. This technique generates a collection of alternative feasible schedules by applying the dispatch heuristic to different sets of randomly perturbed data. The quality of the schedules is then evaluated. Thousands of feasible solutions can be found within minutes. We also formulated an integer programming model that selects a path for each train and maintenance task from a set of alternatives. If all possible paths are considered, then the best schedule found is guaranteed to be optimal. To reduce the size of the model, we explored a reduction technique called 'branch and price'. The method works on small example problems where paths are selected from a predetermined set, but the computation time and memory requirements mean that the method is not suitable for realistic problems. The main advantages of the problem space search method are generality and speed. We are able to model the operations of a variety of rail networks due to the representation of the problem. The generated schedules can be ranked with a user-defined objective measure. The speed at which we produce a range of feasible integrated schedules allows the method to be used in an operational setting, both to create schedules and to test different scenarios. A comparison with simulated current practice on a range of test data sets reveals improvements in total delay of up to 22%.

This project is a creative production that combines image, sound, and narrative. It uses these elements to employ a twist as a device for a paradigm and genre shift in a short film text. My short film introduces a plot that is seemingly linear. Yet, the twist presents a piece of information that reveals the actual non-linear nature of the story, which in turn necessitates the re-interpretation of the plot. The aim of this project is to explore how a twist in a narrative-based short film can alter the cues and perceptions the audience receive from the plot. The project is predominantly practice-based (80%).

Rail track operators have traditionally used manual methods to construct train timetables. Creating a timetable can take several weeks, and so the process usually stops once the first feasible timetable has been found. It is suspected that this timetable is often far from optimal. Existing methods schedule track maintenance once the best train timetable has been determined and allow little or no adjustments to the timetable. This approach almost certainly produces suboptimal integrated solutions since the track maintenance schedule is developed with the imposition of the previously constructed train timetable. The research in this thesis considers operationally feasible methods to produce integrated train timetables and track maintenance schedules so that, when evaluated according to key performance criteria, the overall schedule is the best possible. This research was carried out as part of the Cooperative Research Centre for Railway Engineering and Technologies. We developed a method that uses a local search meta-heuristic called 'problem space search'. A fast dispatch heuristic repeatedly selects and moves a track possessor (train or maintenance task) through the network; this results in a single integrated schedule. This technique generates a collection of alternative feasible schedules by applying the dispatch heuristic to different sets of randomly perturbed data. The quality of the schedules is then evaluated. Thousands of feasible solutions can be found within minutes. We also formulated an integer programming model that selects a path for each train and maintenance task from a set of alternatives. If all possible paths are considered, then the best schedule found is guaranteed to be optimal. To reduce the size of the model, we explored a reduction technique called 'branch and price'. The method works on small example problems where paths are selected from a predetermined set, but the computation time and memory requirements mean that the method is not suitable for realistic problems. The main advantages of the problem space search method are generality and speed. We are able to model the operations of a variety of rail networks due to the representation of the problem. The generated schedules can be ranked with a user-defined objective measure. The speed at which we produce a range of feasible integrated schedules allows the method to be used in an operational setting, both to create schedules and to test different scenarios. A comparison with simulated current practice on a range of test data sets reveals improvements in total delay of up to 22%.