<p>U okviru disertacije, kori&scaron;ćenjem linearnog programiranja, definisani<br />su različiti modeli za optimizaciju monitoringa deponijskog gasa i<br />procedne vode na zatvorenim deponijama. Razvoj modela je baziran<br />na grafičkoj metodi linearnog programiranja i upotrebi softvera<br />GeoGebra. Na osnovu dobijenih rezultata, identifikovani su parametri<br />monitoringa procedne vode kao i obim monitoringa deponijskog gasa<br />i procedne vode. Evaluirani su ekonomski i legislativni efekti<br />modelovanja i uočene značajne mogućnosti u&scaron;tede i unapređenja<br />procesa monitoring zatvorenih deponija.</p> / <p>This doctoral dissertation, by using the linear programming, has defined<br />the various optimization models for the monitoring of landfill gas and<br />leachate at the closed landfills. The development of the model is based<br />on graphical method of linear programming and the usage of GeoGebra<br />software. According to the results, leachate monitoring parameters and<br />landfill gas and leachate monitoring volume have been identified. The<br />economical and legislative effects of the models have also been<br />evaluated, as well as the considerate possibilities for financial saving<br />and improvement of the closed landfill monitoring process.</p>

<div>The practice of project bundling, which involves combining multiple projects into a single multi-project contract, is in increased use at infrastructure agencies. Researchers have shown that this practice potentially reduces project cost but could cause undesirable consequences such as reduced market competition. For this reason, bundling policy needs to be guided by a determination of whether specific projects should be bundled, the bundling strategy in terms of bundle size, bundling combinations, geographical locations, and project scheduling, and the resulting outcome of each strategy in the terms of contract performance (overall cost and time duration, and cost and time overrun). Practitioners seeking answers to these questions continue to be stymied by the lack of quantified relationships between bundling alternatives and the resulting contract performance.</div><div>This dissertation addresses these questions by analyzing empirical data including the costs and durations of highway contracts and projects over a ten-year period. Using a variety of modeling approaches, the dissertation developed models to quantify the effects of bundling-related factors on the key contract performance measures (CPMs). The bundling related factors are contract size, bundle size, project combinations, project similarity and spatial proximity between bundled projects, and the CPMs are project cost and time performance, market competition, and the risks of cost overrun and project delay. Through the modeling process, the dissertation measured the effects of project similarity, economies of scale, economies of bundling, and economies of competition on bundling, and developed a novel technique to measure similarities between projects. Using the developed models, the dissertation then established an optimization framework to identify cost-effective bundling strategies. A greedy approach that minimizes the overall cost in a polynomial time was proposed to obtain heuristic solutions. The outcomes of this dissertation are twofold: first, it provides highway agencies with a quick, convenient and robust tool to design long-term cost-effective bundling strategies for any given pool of candidate projects; secondly, it provides guidelines and directions for future bundling policy formulation or evaluation. </div>

Autonomous electric vehicles are set to replace most conventional vehicles in the near future. Extensive research is being done to improve efficiency at the individual and fleet level. There is much potential benefit in optimizing the deployment and rebalancing of Autonomous Electric Taxi Fleets (AETF) in cities with dynamic demand and limited charging infrastructure. We propose a Fleet Management System with an Online Optimization Model to assign idle taxis to either a region or a charging station considering the current demand and charging station availability. Our system uses real-time information such as demand in regions, taxi locations and state of charge (SoC), and charging station availability to make optimal decisions in satisfying the dynamic demand considering the range-based constraints of electric taxis. We integrate our Fleet Management System with MATSim, an agent-based transport simulator, to simulate taxis serving real on-demand requests extracted from the San Francisco taxi mobility dataset. We found our system to be effective in rebalancing and ensuring efficient taxi operation by assigning them to charging stations when depleted. We evaluate this system using different performance metrics such as passenger waiting time, fleet efficiency (taxi empty driving time) and charging station utilization by varying initial SoC of taxis, frequency of optimization and charging station capacity and power.

Autonomous electric vehicles are set to replace most conventional vehicles in the near future. Extensive research is being done to improve efficiency at the individual and fleet level. There is much potential benefit in optimizing the deployment and rebalancing of Autonomous Electric Taxi Fleets (AETF) in cities with dynamic demand and limited charging infrastructure. We propose a Fleet Management System with an Online Optimization Model to assign idle taxis to either a region or a charging station considering the current demand and charging station availability. Our system uses real-time information such as demand in regions, taxi locations and state of charge (SoC), and charging station availability to make optimal decisions in satisfying the dynamic demand considering the range-based constraints of electric taxis. We integrate our Fleet Management System with MATSim, an agent-based transport simulator, to simulate taxis serving real on-demand requests extracted from the San Francisco taxi mobility dataset. We found our system to be effective in rebalancing and ensuring efficient taxi operation by assigning them to charging stations when depleted. We evaluate this system using different performance metrics such as passenger waiting time, fleet efficiency (taxi empty driving time) and charging station utilization by varying initial SoC of taxis, frequency of optimization and charging station capacity and power.

The demand for aviation has been steadily growing over the past few decades and will keep increasing in the future. The anticipated growth of traffic demand will cause the current airspace system, one that is already burdened by heavy operations and inefficient usage, to become even more congested than its current state. Because busy airports in the United States (U.S.) are becoming "bottlenecks" of the National Airspace System (NAS), it is of great importance to discover the most efficient means of using existing facilities to improve airport operations. This dissertation aims at designing an efficient airport surface operations management system that substantially contributes to the modernized NAS. First, a global comparison is conducted in the major airports within the U.S. and Europe in order to understand, compare, and explore the differences of surface operational efficiency in two systems. The comparison results are then presented for each airport pair with respect to various operational performance metrics, as well as airport capacity and different demand patterns. A detailed summary of the associated Air Traffic Management (ATM) strategies that are implemented in the U.S. and Europe can be found towards the end of this work. These strategies include: a single Air Navigation Service Provider (ANSP) in the U.S. and multiple ANSPs in Europe, airline scheduling and demand management differences, mixed usage of Instrument Flight Rule (IFR) and Visual Flight Rules (VFR) operations in the U.S., and varying gate management policies in two regions. For global comparison, unimpeded taxi time is the reference time used for measuring taxi performance. It has been noted that different methodologies are currently used to benchmark taxi times by the performance analysis groups in the U.S. and Europe, namely the Federal Aviation Authority (FAA) and EUROCONTROL. The consistent methodology to measure taxi efficiency is needed for the facilitation of global benchmarking. Therefore, after an in-depth factual comparison conducted for two varying methodologies, new methods to measure unimpeded taxi times are explored through various tools, including simulation software and projection of historical surveillance data. Moreover, a sophisticated statistical model is proposed as a state-of-the-art method to measure taxi efficiency while quantifying the impact of various factors to taxi inefficiency and supporting decision-makers with reliable measurements to improve the operational performance. Lastly, a real-time integrated airport surface operations management (RTI-ASOM) is presented to fulfil the third objective of this dissertation. It provides optimal trajectories for each aircraft between gates and runways with the objective of minimizing taxi delay and maximizing runway throughput. The use of Mixed Integer Linear Programming (MIP) formulation, Dynamic Programming for decomposition, and CPLEX optimization can permit the use of an efficient solution algorithm that can instantly solve the large-scale optimization problem. Examples are shown based on one-day track data at LaGuardia Airport (LGA) in New York City. In additional to base scenarios with historical data, simulation through MATLAB is constructed to provide further comparable scenarios, which can demonstrate a significant reduction of taxi times and improvement of runway utilization in RTI-ASOM. By strategically holding departures at gates, the application of RTI-ASOM also reduces excess delay on the airport surface, decreases fuel consumption at airports, and mitigates the consequential environmental impacts.

The costs of patient care reached a new height. Poor management of patient flows in hospitals lead to unnecessary waiting time, a low degree of capacity utilization and expensive needless treatments. In the beginning of this paper a shortly overview of health care optimization research is shown, which leads to the implementation of interdisciplinary clinical pathways to improve the patient flow. Based on this the structure of scheduling focused clinical pathways is described. After that, a mixed integer linear programming model is shown, which is able to schedule these pathways. In the end the model is verified by an instance of a clinical pathway.

This thesis is based on Gordon-Schaefer model, and assesses Argentine shortfin squid¡¦s stock by using the data of Southwest Atlantic from FAO between 1983 and 2009. First, estimate the equilibrium level of the open-access fishery and dynamic optimization fishery and compare to each other. Then estimate annual Argentine shortfin squid¡¦s stock size, comparing the stock size with the equilibrium level of the two fishery models. The result is that Argentine shortfin squid¡¦s stock size has no crisis of extinction now in Southwest Atlantic. In addition, simulate Argentine shortfin squid¡¦s stock size under management and no management status in the future. The result is that it will make the Argentine shortfin squid sustainable development under dynamic optimization fishery, and this fishery model will be a good management. Finally, this thesis based on the catch of Southwest Atlantic Argentine shortfin squid, which we figure out the fluctuation of catch by literatures, and do the sensitivity analysis.

Sergestid Shrimp contains rich nutrition, regards as a high-class aquatic product in Japan. The management of the catch has come into operation, and it¡¦s led the price raising and the output value increasing rapidly when the establishment of TungKung producer organization of the Sergestid Shrimp in 1993 and it also has become the important seasonal fishery in the southwestern coast of Taiwan. This study is based on the fundamental model of fish dynamic- Gordon Schaefer Model, to discuss the equilibrium values for the optimal conduction of open access and dynamic optimization, and to do the comparative statics analysis. By applying the data provided by Fisheries Research Institute, the evaluation of the variation are under both conductions were available, and in additions, the sensitivity analysis had been done by assuming all bio-economics parameters varied within a reasonable range. The study can figure out the fact that the management of TungKang producer organization of the Sergestid Shrimp with the notion of the sustainable administration by the derivation of theoretical model and the simulate analysis of historical data, and the conclusions of analysis are consistency. Furthermore, the study discusses the fishery management policies of TungKung Sergestid Shrimp. I hope the management policies of TungKung producer organization of the Sergestid Shrimp could be popularized in the related industry.

This dissertation investigates three economic aspects of the climate change issue: optimal allocation of investment between adaptation and mitigation, impacts on a ground water dependent regional agricultural economy and effects on global food insecurity. This is done in three essays by applying mathematical programming. In the first essay, a modeling study is done on optimal temporal investment between climate change adaptation and mitigation considering their relative contributions to damage reduction and diversion of funds from consumption and other investments. To conduct this research, we extend the widely used Integrated Assessment Model?DICE (Dynamic Integrated Climate Economy) adding improved adaptation modeling. The model results suggest that the joint implementation of adaptation and mitigation is welfare improving with a greater immediate role for adaptation. In the second essay, the research focuses on the ground water dependent agricultural economy in the Texas High Plains Region. A regionally detailed dynamic land allocation model is developed and applied for studying interrelationships between limited natural resources (e.g. land and groundwater), climate change, bioenergy demands and agricultural production. We find out that the effect varies regionally across hydrologically heterogeneous regions. Also, water availability has a substantial impact on feedstock mix. In terms of biofuel feedstock production, the model results show that limited water resource cannot sustain expanded corn-based ethanol production in the future. In the third essay, a Computable General Equilibrium (CGE) model is applied in an attempt to study potential impacts of climate change on global food insecurity. Our results show that climate change alters the number of food insecure people in a regionally different fashion over time. In general, the largest increase of additional food insecure population relative to the reference case (no climate change) is found in Africa and South Asia, while most of developed countries will benefit from climate change with a reduced proportion of food insecure population. In general, climate change affects world agricultural production and food security. Integrated adaptation and mitigation strategy is more effective in reducing climate change damages. However, there are synergies/trade-offs between these two options, particularly in regions with limited natural resources.

Dans un monde industriel marqué par un contexte économique difficile, les entreprises se doivent d’étudier toutes les possibilités de réduction de coûts et d’optimisation de leur chaîne logistique. Un des champs récents d’optimisation développé dans la littérature concerne le concept de logistique inverse. Cette logistique représente la gestion des flux traversant une chaîne logistique dans le sens inverse des flux traditionnels. On y retrouve des activités liées au recyclage, à la réparation ou encore à la réutilisation de produits. Au sein de la Chaire Supply Chain, nous nous sommes donc intéressés à l’optimisation de la gestion de ces flux de retours, avec les contenants réutilisables comme objet d’étude intéressant pour nos différents partenaires. Dans ce sens, après avoir passé en revue la littérature sur le concept général de la logistique inverse, nous développons un ensemble de modèles recouvrant les combinaisons mono ou multi niveaux, mono ou multi périodes et mono ou multi contenants afin d’optimiser ces retours au sein de chaînes logistiques déjà définies. Ces modèles sont par la suite appliqués, soit fictivement pour un des modèles mono-période résolu grâce à une heuristique de décomposition développée pour des réseaux logistiques de grande taille, soit réellement chez nos partenaires pour les modèles multi-périodes résolus de façon exacte. Le but de ces applications étant d’utiliser ces modèles théoriques dans un contexte réel d’entreprise et d’en dégager les possibles bénéfices économiques mais également environnementaux grâce à la prise en compte des émissions liées au transport et au cycle de vie de ces contenants. / In an industrial world touched by a complicated economic environment, companies need to explore all opportunities for cost reduction and supply chain optimization. A recent optimization field developed in the literature concerns the concept of reverse logistics. This concept deals with the flows management through a supply chain in the opposite direction to the traditional one. It includes activities related to recycling, repair or products reuse. In partnership with the industrial of the “Chaire Supply Chain”, we are interested in optimizing these reverse flows by focusing more particularly on reusable containers. For that, we propose a literature review on the general concept of reverse logistics and develop a set of models covering combinations between single and multi-levels, single and multi-periods and single and multi-containers problems in order to optimize this type of returns within already defined supply chains. These models are then applied, either in a fictive way for a single-period one solved by a decomposition heuristic proposed for large logistics networks, or in a real way for multi-period models solved exactly and applied to our partners problematic. The purpose of these applications is to use these theoretical models in a real business in order to identify economic benefits but also environmental ones by taking into account emissions from these containers transportation and manufacturing.