Chiu Chung-Bun. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1986. / Includes bibliographical references (leaf 85).

This paper presents a mathematical sizing algorithms of a stand alone and grid-connected photovoltaic-battery system for a residential house. The objective is to minimize the total storage capacity with cost of electricity. The proposed methodology is based on a Linear and Non-linear programming involving a real data collected through one year with reference to Hradec Kralove meteorological data and typical load profile in Czech Republic. The algorithm jointly optimizes the sizes of the photovoltaic and the battery systems by adjusting the battery charge and discharge cycles according to the availability of solar resource and a time-of-use tariff structure for electricity. The results show that jointly optimizing the sizing of battery and photovoltaic systems can significantly reduce electricity imports and the cost of electricity for the household. However, the optimal capacity of such photovoltaic battery varies strongly with the electricity consumption profile of the household, and is also affected by electricity and battery prices.

This paper presents a mathematical sizing algorithms of a grid-connected photovoltaic-battery system for a residential house. The objective is to minimize the total storage capacity with cost of electricity. The proposed methodology is based on a Linear and Non-linear programming. We have presents results from a existing PV panel FS-4115-3 for the given climatic conditions and the electricity use profile. Measurements for whole household electricity consumption have been obtained over a period of two months. They were all obtained at one hour interval. The algorithm jointly optimizes the sizes of the photovoltaic and the battery systems by adjusting the battery charge and discharge cycles according to the availability of solar resource and a time-of-use tariff structure for electricity. The results show that jointly optimizing the sizing of battery and photovoltaic systems can significantly reduce electricity imports and the cost of electricity for the household.

Doctor of Philosophy / Department of Animal Sciences and Industry / Joel M. DeRouchey / A total of 7,061 finishing pigs were used in 7 experiments. Experiment 1 investigated the effects of withdrawing high-fiber ingredients prior to marketing to optimize growth performance, carcass yield, and carcass fat quality. Switching pigs from a high-fiber to a low-fiber corn-soy diet approximately 15 to 19 d before slaughter restored carcass yield and partially decreased carcass fat IV compared to pigs fed the high-fiber diet until slaughter. Experiment 2 studied 30% distillers dried grains with solubles (DDGS) and 5% added fat prior to slaughter on growth performance and carcass characteristics. Adding 5% fat to finishing pig diets containing 30% DDGS approximately 20 d before slaughter improved ADG and G:F but did not overcome the reduction in carcass yield from feeding DDGS. Experiment 3 investigated the Cu source on growth performance and carcass characteristics. Increasing dietary Cu in high byproduct diets improved growth and feed intake, resulting in increased final BW and HCW for pigs fed both Cu sources. Experiment 4 examined added Cu and standardized ileal digestible (SID) lysine (Lys) level on growth performance, carcass characteristics, and carcass fat quality. Feeding 150 mg/kg Cu to pigs in the 100% SID Lys requirement diet had improved growth but in the 85 or 92.5% SID Lys requirement diet no response to added Cu was found. Furthermore, increasing SID Lys increased ADG and HCW, but added Cu did not influence growth when feeding low SID Lys. Experiment 5 investigated diet ingredient type and added Cu on growth performance, carcass characteristics, gross energy digestibility, and small intestine histology and gene expression. When comparing diet type and added Cu, pigs fed a byproduct diet with DDGS and bakery meal tended to have lower G:F and reduced HCW compared to pigs fed a corn-soy diet. Adding Cu did not influence growth or carcass characteristics. However, adding Cu to the byproduct diet improved gross energy digestibility and decreased the crypt depth in the distal small intestine. Finally, a linear programming model was developed as a decision tool for commercial swine producers to help guide pig flow decisions to maximize the return to the operation.

Hill farming systems in Scotland are the result of long evolution and adaptation to financial, social and political changes. Farming in the hills is a major contributor to rural industry and plays an important role in the economy, environment and social cohesion of these areas. However, it is fragile and has been dependent for many decades on high and continued levels of support payments. Agricultural land managers in these hill areas are also under increasing pressure from the other land use groups whose interests lie outside farming. With recent agricultural reforms, shifts in policy orientations regarding land use and changes in support, the future role of hill farming remains uncertain. This thesis sets out to examine the role of hill farming in this context of change, by investigating how hill farmers respond to changing policy, by understanding what other interested stakeholders expect from the hills, and exploring how hill farmers may have to adapt their farming system in response to these changes and expectations. Using an adaptive conjoint analysis method, stakeholders’ expectations have been assessed. Multivariate analysis and participative research with hill farmers have also been carried out, to typify their management responses to policy changes, using the 2003 CAP reform as an example. Stakeholders’ expectations and farmers’ types were then used in a linear programming optimisation model, to explore how hill farmers can maximise their financial margins under different policy and market change scenarios, and how their motivation is a drive towards adaptation. The results suggest that whilst livestock production is identified by stakeholders as one of the most important features for the hill areas, the continuity of livestock farming in the hills is threatened, as hill farmers are strongly affected by policy and market changes. This research also shows that there is a strong diversity in hill farming systems and in hill farmers’ management styles and motivations. That, perhaps, is one of the most important factors to acknowledge when formulating policies. This research also highlights the vulnerability of hill farming businesses (especially hill cattle production) to market price volatility, policy, subsidies and support changes, making it difficult for any hill farmer to withstand these fluctuations. Although different land uses, such as planting forestry, potentially bring substantial economic benefits, they are dependent upon many other restricting factors, including government grants, and require long-term commitment before benefits are seen. Integration of different land uses and productions could be one economic option for these areas, but a set of measures, perhaps including livestock-linked subsidies that recognise the diversity of hill farmers is needed, as well as options for hill farmers to be able to provide other public goods. Unless there is stability in market prices, a policy drive towards increasing efficiency, adequate subsidies and support and more readily attractive diversification options, including the provision of other ecosystem services linked to these grassland systems, this thesis suggests that there is a danger of hill land abandonment, a further decrease in hill farming activity, leading eventually to a decline in rural areas, not unlike many other marginal hill and mountain areas in the UK and Europe.

Many real-world optimisation problems are discrete in nature. Although recent rapid developments in computer technologies are steadily increasing the speed of computations, the size of an instance of a hard discrete optimisation problem solvable in prescribed time does not increase linearly with the computer speed. This calls for the development of new solution methodologies for solving larger instances in shorter time. Furthermore, large instances of discrete optimisation problems are normally impossible to solve to optimality within a reasonable computational time/space and can only be tackled with a heuristic approach. In this thesis the development of so called matheuristics, the heuristics which are based on the mathematical formulation of the problem, is studied and employed within the variable neighbourhood search framework. Some new variants of the variable neighbourhood searchmetaheuristic itself are suggested, which naturally emerge from exploiting the information from the mathematical programming formulation of the problem. However, those variants may also be applied to problems described by the combinatorial formulation. A unifying perspective on modern advances in local search-based metaheuristics, a so called hyper-reactive approach, is also proposed. Two NP-hard discrete optimisation problems are considered: 0-1 mixed integer programming and clustering with application to colour image quantisation. Several new heuristics for 0-1 mixed integer programming problem are developed, based on the principle of variable neighbourhood search. One set of proposed heuristics consists of improvement heuristics, which attempt to find high-quality near-optimal solutions starting from a given feasible solution. Another set consists of constructive heuristics, which attempt to find initial feasible solutions for 0-1 mixed integer programs. Finally, some variable neighbourhood search based clustering techniques are applied for solving the colour image quantisation problem. All new methods presented are compared to other algorithms recommended in literature and a comprehensive performance analysis is provided. Computational results show that the methods proposed either outperform the existing state-of-the-art methods for the problems observed, or provide comparable results. The theory and algorithms presented in this thesis indicate that hybridisation of the CPLEX MIP solver and the VNS metaheuristic can be very effective for solving large instances of the 0-1 mixed integer programming problem. More generally, the results presented in this thesis suggest that hybridisation of exact (commercial) integer programming solvers and some metaheuristic methods is of high interest and such combinations deserve further practical and theoretical investigation. Results also show that VNS can be successfully applied to solving a colour image quantisation problem.

This research deals with the optimization of metrology and calibration problems. The optimization involved here is the application scientifically sound operations research techniques to help in solving the problem intended optimally or semi-optimally with a practical time frame. The research starts by exploring the subject of measurement science known as metrology. This involves defining all the constituents of metrology facilities along with their various components. The definitions include the SI units’ history and structure as well as their characteristics. After that, a comprehensive description of most of the operations and parameters encountered in metrology is presented. This involves all sources of uncertainties in most of the parameters that affect the measurements. From the background presented and using all the information within it; an identification of the most important and critical general problems is attempted. In this treatment a number of potential optimization problems are identified along with their description, problem statement definition, impact on the system and possible treatment method. After that, a detailed treatment of the scheduling problem, the calibration interval determination problem and the average outgoing quality problem is presented. The scheduling problem is formulated and modelled as a mixed integer program then solved using LINGO program. A heuristic algorithm is then developed to solve the problem near optimally but in much quicker time, and solution is packaged in a computer program. The calibration interval problem treatment deals with the determination of the optimal CI. Four methods are developed to deal with different cases. The cases considered are the reliability target case, the CI with call cost and failure cost of both first failure and all failures and the case of large number of similar TMDEs. The average out going quality (AOQ) treatment involves the development two methods to assess the AOQ of a calibration facility that uses a certain multistage inspection policy. The two methods are mathematically derived and verified using a simulation model that compares them with an actual failure rate of a virtual calibration facility.

The Marine infantryman is carrying too much weight in combat. This thesis analyzes the trade-offs between individual load weights and the value that a Distributed Operations squad receives from the equipment its members carry. We use multiple objective decision analysis principles to help determine the coefficients for an integer linear programming model. The optimization model prescribes equipment assignment to individual positions that maximizes squad mission success while meeting target weights for the individual Marine. Our findings indicate that significant improvements can be made to the Marine's combat load weight and equipment composition. The optimization model provides the squad with a more efficient combination of equipment while reducing the average weight of the combat load by more than 19 percent for both the assault load and the approach march load. Also, by balancing the loads across the members of the squad, the model reduces the variation of weight across the squad positions from as much as 38 percent to less than 2 percent for all loads. By examining the trade space between equipment weight and equipment value, we assist in the creation of future Marine Corps doctrine by providing senior Marine leaders a starting point analysis for addressing this difficult problem.

Approved for public release, distribution is unlimited / The Basic School (TBS) is the first school assignment for all Marine Officers. While assigned to TBS unrestricted ground officers compete for and are assigned a Military Occupational Skill (MOS). The process of educating the Marine Officers about the different MOSs is primarily accomplished by word of mouth at MOS Mixers (social events) and one-on-one discussions. The assignment of the MOS to the Marine Officer is based on the officer's lineal standing within his/her company. Officers are ranked lineally based on a composite score of academic and leadership grades. To ensure a quality distribution of officers into MOSs, the company is divided into thirds (Top, Middle, Bottom) and the vacancies assigned to the company are divided into thirds (Top, Middle, Bottom). Officers compete for an MOS within their assigned third. The current assignment system has remained virtually unchanged over the last thirty years. It is a mostly manually process that provides little visibility of the data, and does not utilize automated information tools for report generation of statistical information. This joint thesis team has developed a Two-Tier Client/Server Information Management System for use by the lieutenants and staff officers of The Basic School and it is called MyMOS. This system was developed using current industry standards that are compliant with those of the Department of Defense. It is the first of its kind at TBS and is designed to be employed as an operational system. MyMOS was designed with an interface that would maximize acceptance and reduce total ownership cost. / Captain, United States Marine Corps / Lieutenant Colonel, United States Marine Corps

Approved for public release; distribution is unlimited / "During four rounds of base realignment and closure (BRAC), the United States Army reduced its military infrastructure to meet its future national security and military requirements. After each round's closures and realignments were approved, all necessary actions (excluding some environmental cleanup) had to be scheduled over six years. The United State Army used an integer linear program, BRACAS (Base Realignment and Closure Action Schedule), to help guide the implementation of the 1995 round's actions. BRACAS schedules closure and realignment actions, and maximizes the net present value NPV of total cost savings while adhering to an annual budget and other constraints. This thesis updates BRACAS. Its main contribution is a more realistic inclusion of environmental cleanup costs. Using data based on the Army's 1995 round and letting BRACAS pick its yearly (1996-2001) budget, the refined BRACAS finds a 20-year NPV of $6 ,346 million. We examine how closures and the 20-year NPV are changed for several scenarios where we restrict yearly budgets and alter the inclusion of environmental cleanup costs."--p. i. / Major, Bahrain Defense Force (BDF)