Stochastic programming is a mathematical technique for decision making under uncertainty using probabilistic statements in the problem objective and constraints. In practice, the distribution of the unknown quantities are often known only through observed or simulated data. This dissertation discusses several methods of using this data to formulate, solve, and evaluate the quality of solutions of stochastic programs. The central contribution of this dissertation is to investigate the use of techniques from simulation and statistics to enable data-driven models and methods for stochastic programming. We begin by extending the method of overlapping batches from simulation to assessing solution quality in stochastic programming. The Multiple Replications Procedure, where multiple stochastic programs are solved using independent batches of samples, has previously been used for assessing solution quality. The Overlapping Multiple Replications Procedure overlaps the batches, thus losing the independence between samples, but reducing the variance of the estimator without affecting its bias. We provide conditions under which the optimality gap estimators are consistent, the variance reduction benefits are obtained, and give a computational illustration of the small-sample behavior. Our second result explores the use of phi-divergences for distributionally robust optimization, also known as ambiguous stochastic programming. The phi-divergences provide a method of measuring distance between probability distributions, are widely used in statistical inference and information theory, and have recently been proposed to formulate data-driven stochastic programs. We provide a novel classification of phi-divergences for stochastic programming and give recommendations for their use. A value of data condition is derived and the asymptotic behavior of the phi-divergence constrained stochastic program is described. Then a decomposition-based solution method is proposed to solve problems computationally. The final portion of this dissertation applies the phi-divergence method to a problem of water allocation in a developing region of Tucson, AZ. In this application, we integrate several sources of uncertainty into a single model, including (1) future population growth in the region, (2) amount of water available from the Colorado River, and (3) the effects of climate variability on water demand. Estimates of the frequency and severity of future water shortages are given and we evaluate the effectiveness of several infrastructure options.

No description available.

No description available.

The master thesis is focused on implementing a module for batch traceability into the existing SCADA system MagmaView. First, the theoretical part is dedicated to the research of ANSI/ISA-95 standard and traceability problematics in the process industry. First, the practical part analyses the design of the data model and model for user interaction. The next topic is the implementation of the mentioned models using several software tools such as the graphical environment of MagmaView, Groovy scripting, and communication with SQL database. Part of the implementation is also a testing project simulating a simple production process and the needs of the operator to work with the batches.

Yes / Scheduling is an important element that has a major impact on the efficiency of all manufacturing processes. It plays an important role in optimising the manufacturing times and costs resulting in energy efficient processes. It has been estimated that more than 75% of manufacturing processes occur in small batches. In such environments, processes must be able to perform a variety of operations on a mix of different batches. Batch-job scheduling optimisation is the response to such low batch manufacturing problems. The optimisation of batch-job process scheduling problem is still a challenge to researchers and is far from being completely solved due to its combinatorial nature. In this paper, a novel hybrid heuristic (HybH) solution approach for batch-job scheduling problem is presented with the objective of optimising the overall Makespan (Cmax). The proposed HybH is the combination of Index Based Heuristic (IBH) and the Finished Batch-Job (FBJ) process schedule. The heuristic assigns the first operation to a batch-job using IBH and the remaining operations on the basis FBJ process schedule. The FBJ process schedule gives priority to the batch-job with early finished operations, without violating the constraints of process order. The proposed HybH is explained with the help of a detailed example. Several benchmark problems are solved from the literature to check the validity and effectiveness of the proposed heuristic. The presented HybH has achieved batch-job process schedules which have outperformed the traditional heuristics. The results are encouraging and show that the proposed heuristic is a valid methodology for batch process scheduling optimisation.

Accelerated bridge construction (ABC) has become a popular alternative to using traditional construction techniques in new bridge construction and existing bridge deck replacement because of the reduction of time spent in field activities. A key feature of bridges built using ABC techniques is the extensive use of prefabricated components. Prefabricated components are joined in the field using small volume closure pours involving high performance materials (steel and concrete) to ensure adequate transfer of forces between components. To date, the materials developed for closure pours have been based on proprietary components, so a need has arisen for development of mixes that use generic components. The goal of this research was to create a method to develop concrete mixtures that are designed using generic constituents and that satisfy performance requirements of accelerated bridge construction closure pours in New England, primarily high early strength and long-term durability. Two concrete mixtures were developed with a primary goal of reaching high-early strength while maintaining constructability. The secondary goal of the concrete mixtures was to be durable; therefore, measures were taken during the development of the concrete mixture to generate a mixture that also had durable properties.

L'usage excessif des routes peut entraîner de nombreux inconvénients dont la pollution, les accidents et la congestion. Une solution accessible à court terme consiste à mettre en œuvre des systèmes de gestion de trafic. Dans ce cadre, nous proposons un formalisme, appelé Réseaux de Petri Lots Triangulaire, qui permet la modélisation et la simulation du trafic routier au niveau mésoscopique comme un système à événements discrets. Le RdPLots Triangulaire permet ainsi de décrire les caractéristiques globales du trafic routier: flux, densité et vitesse à travers la proposition d'une relation flux-densité triangulaire. Cette relation implique une modification de la dynamique des lots. Cette dynamique permet maintenant de représenter les deux états du trafic routier à savoir fluide et congestionné ainsi que les trois régimes dédiés au comportement libre, congestion et décongestion. Le calcul des flux instantanés des transitions est à présent réalisé par une méthode basée sur la technique de programmation linéaire en ajoutant une contrainte qui prend en compte l'état et le régime des lots. Pour modéliser des stratégies de contrôle telles que la variation de la vitesse limite (VSL), nous avons intégré au RdPLots Triangulaire des événements contrôlés qui permettent le changement de la vitesse maximale d'une place lot et le flux maximal d'une transition continue ou lot. Tous ces apports théoriques sont implémentés dans un logiciel que nous avons appelé SimuleauTri, sous lequel nous avons étudié des portions d'autoroute à partir des données réelles. Les résultats de simulation sont proches des mesures effectuées sur le terrain, et montrent la pertinence de RdPLots Triangulaire. / The excessive use of roads can cause many adverse effects including pollution, insecurity and congestion. The available short-term solution is the implementation of traffic management systems which optimize the flow and reduce congestion without needing additional infrastructures. In this context, we proposed a new formalism, called Triangular Batches Petri Nets (Triangular BPN), which combines modeling and simulation of traffic in mesoscopic level as a discrete event system. The Triangular BPN describing the overall characteristics of the road traffic such as flow, density, speed by representing a new triangular relation flow-density. This relation implies the modification of batches dynamic, which is now used to represent the two road traffic states : fluid and congested, as well as the three behaviors :free, congestion and decongestion. The calculation of the instantaneous firing flows is achieved by adding a constraint that takes into account the state and behavior of batches. A set of controlled events integrated to the Triangular BPN, that allow the variation of the maximum speed of batch place and the maximum flow of batch and continuous transition. These controlled events used to model the control strategies, such as variable speed limit (VSL). All these theoretical contributions implemented in a software that is called SimuleauTri and used to study a motorway portions from real data. The simulation results are close to the measurements on the ground and show the pertinence of Triangular BPN.