Robert E. Kohn. / Includes index. / Bibliography: p. [237]-244.

by Robert M. Freund. / "October 1984." / Bibliography: p. 20-21.

Master of Science / Department of Agricultural Economics / Tian Xia / China has always been one of the world’s largest grain producers, and Jilin is the largest grain-producing province in China. According to the Report on the Work of the Government 2018, the yield per mu (0.165 acre) has remained the first of the country for the past five years; and the grain commodity rate, the volume of transfers and the possession per capita have remained at the forefront of the country, making a significant contribution to ensuring national food security. This study is to compare efficient allocation of resources through designing a linear programming model with current allocation of resources to find out potential improvements and policy suggestions for future agricultural structure, rational cultivation of grains and market prediction for Jilin, China. In addition, this study examines what role the government regulations play in the grain production in China and how the trade war affects the grain production.

Approved for public release; distribution is unlimited / Includes supplemental material, embedded in this pdf. See page 46 of document to read instructions for accessing supplemental material. / The fuel planning for U.S. Naval operations at sea is reactive and relies upon pen and paper calculations. Decisions on where and when to refuel are complex and need a Decision Support System (DSS) to help planners maximize the benefits of the limited fuel resource. This thesis defines requirements and outlines a feasible design to develop a Naval Fuel Management System (NFMS). The variables that fuel planning rely upon are not just ship course and speed, but also the weather at the time a ship travels through a particular area. The most efficient plant configuration plays a factor in the fuel plan as well. Additionally, there are numerous ports and oilers available at any given time. Up-to-date accurate weather forecast databases are available, predicting currents and winds, which will affect the ship in the future. Fuel burn charts have been developed for each ship class outlining the most efficient plant configuration for given speeds. Transportation analysis has shown that an optimal path exists for this class of complex problems. By combining these technologies into one system, an application can be developed to accurately plan fueling operations in the future, making Navy refueling more efficient. / US Navy (USN) author

No description available.

This thesis presents an application of linear programming to the question of efficient log allocation in the forest industry of British Columbia. Current procedures for allocating logs among alternative utilization processes are discussed and it is suggested that a more efficient allocation might be obtained through a systematic approach to the problem. The economic necessity of improving net returns to the log supply is emphasized. A linear programme log-allocation model is presented, based on an integrated-industry in the coastal region of British Columbia. The model encompasses three main categories of log-use, namely sawmilling, plywood production and pulp production, and demonstrates how a given supply of logs may be optimally distributed among these structurally different log-conversion processes. Emphasis throughout this study is on the structure of the linear programme model, although considerable effort was directed to obtaining realistic data. Solutions of the model, obtained through the services of the Computing Centre at the University of British Columbia, are discussed, and a superficial comparison is made with actual log allocation in the industry. Modifications of the model to suit the log-allocation problem faced by an individual firm in the short-run are discussed and normal comparative-statics applications are considered. It is pointed out that many of the simplifying assumptions in the model may be relaxed. However, the main limitation to its practical application by industry and government lies in the quality and type of data available. In this respect it is suggested that the linear programme model of this thesis provides a valuable guide to the production data required to improve economic efficiency in the forest industry. / Arts, Faculty of / Vancouver School of Economics / Graduate

The presence of imprecision in parameter specification of water resources management problems leads to the formulation of fuzzy programming models. This thesis presents the formulation of a two-reservoir system problem as a fuzzy L.P. model. The aim is to determine if larger monetary benefits, over and above the usual benefits, can be obtained from the system. The other aim is to determine if desired industrial and domestic water allocations, as well as outflows for selected periods can be achieved. The problem is formulated as a conventional L.P. model. Then selected water allocations and outflows are fuzzified resulting in a fuzzy L.P. model. The alternative fuzzy L.P. model is also presented. Monetary benefits larger than those from the conventional L.P. were obtained through the fuzzy L.P. model. The desired water allocations and outflows were also realised for selected periods. Sensitivity information was obtained for fuzzy and non-fuzzy constraints. The alternative fuzzy L.P. model did not give additional valuable information than that obtained from the initial fuzzy L.P. model. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

The human gut microbiome exists as a community of microorganisms in symbiosis with its host. Prebiotics are functional compounds that modulate this microbial community, promoting the growth and activity of bacteria that are beneficial to human health. Resistant starches (RS), a subclass of prebiotics, are compounds linked to a number of host-beneficial effects when included in human diets. Understanding how RS shapes gut flora composition and function is crucial to understanding these effects; however, these effects are clouded by the complexity of the microbiome’s interactions. Comprehensively characterizing microbiome shifts as the result of prebiotics is an intriguing bioanalytical problem. In the thesis project, I hypothesize that: RS changes microbiome biochemical pathway expression community-wide and at different taxonomic levels; that RS forms will affect microbiome bacterial taxonomic distribution; and that a linear programming optimization approach can parsimoniously distribute ambiguous peptide abundances amongst their constituent species, leading to different interpretations of functional and structural characteristics in microbiome metaproteomics data. To address these hypotheses, the thesis project utilizes a combined metaproteomics and bioinformatics approach. The Figeys lab-developed RapidAIM bioanalytical assay is deployed to generate label-free mass spectrometry metaproteomics data, testing for these effects experimentally. Further, Cerberus, a bioinformatics platform for microbiome metaproteomics analyses, was developed to integrate workflows from different software sources into a unified pipeline. Cerberus also implements a novel linear optimization approach addressing the shared-peptide problem. Through experimental data analyses using Cerberus, microbiomes encountering RS showed concerted taxonomic shifts, general and specific functional modulations linked to these taxonomic changes, and a significantly variable pathway expression profile for host-beneficial microbiome processes. The peptide-species linear optimization procedure demonstrates how naïve approaches to the shared-peptide problem greatly skew downstream taxonomic and functional analyses in metaproteomics experiments, marking an important consideration for microbiome studies seeking to resolve taxon-specific alterations.

Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

The design of a chilled water plant involves selecting the size and type of chillers to be employed and determining the operating strategy. The types may include both gas engine and electric motor driven chillers. The issues that have to be considered in the selection problem are to incorporate external and internal factors into the decision making. External factors may include the utility rate schedules, the cooling load profile, and the outdoor temperature profile. Internal factors may include the chiller performance characteristics, initial and maintenance costs, and the chiller(s) operating strategy. A mathematical model representing the chilled water plant design problem is developed. The problem is approached as a mixed integer linear programming problem where non-linear chiller performance curves are transformed into linear constraints through the use of integer variables. The optimization task is to select the best cooling plant configuration and operating strategy to minimize life cycle cost. A solution procedure is developed which decomposes the optimization problem to reduce extensive computation time. Two case studies are provided to investigate the implementation of the mathematical model. / Master of Science