9,833 research outputs found

    Is Cutting the GST the Best Approach?

    Get PDF
    The government of Canada has reduced the Goods and Services Tax (GST) rate by 2-percentage points over the past several years. This tax measure seems to be welcomed by the public and some public policy observers; however, it is also associated with certain economic and social costs. This paper aims to assess the rightness of the GST reduction. To that end, the paper summarizes research findings regarding economic costs and levels of distortion associated with alternate tax measures. The paper also contrasts Canadaโ€™s reliance on consumption taxes with general trends prevailing in other industrialized countries. The analysis shows that taxing consumption is one of the most economically effective methods of generating government revenues, whereas the reduction of consumption taxes yields the least optimal economic pay-off compared to other tax measures. The growing importance of value-added taxation is the clearest tax policy trend in the OECD countries, whereas reducing the GST rate will further diminish the importance of consumption taxes in Canada with no noticeable dollar value savings for households.consumption taxes, GST, Goods and Services Tax, composition of government revenue

    2์ฐจ์› 2๋‹จ๊ณ„ ๋ฐฐ๋‚ญ๋ฌธ์ œ์— ๋Œ€ํ•œ ์ •์ˆ˜๊ณ„ํš๋ชจํ˜• ๋ฐ ์ตœ์ ํ•ด๋ฒ•

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์‚ฐ์—…๊ณตํ•™๊ณผ, 2021. 2. ์ด๊ฒฝ์‹.In this thesis, we study integer programming models and exact algorithms for the two-dimensional two-staged knapsack problems, which maximizes the profit by cutting a single rectangular plate into smaller rectangular items by two-staged guillotine cuts. We first introduce various integer programming models, including the strip-packing model, the staged-pattern model, the level-packing model, and the arc-flow model for the problem. Then, a hierarchy of the strength of the upper bounds provided by the LP-relaxations of the models is established based on theoretical analysis. We also show that there exists a polynomial-size model that has not been proven yet as far as we know. Exact methods, including branch-and-price algorithms using the strip-packing model and the staged-pattern model, are also devised. Computational experiments on benchmark instances are conducted to examine the strength of upper bounds obtained by the LP-relaxations of the models and evaluate the performance of exact methods. The results show that the staged-pattern model gives a competitive theoretical and computational performance.๋ณธ ๋…ผ๋ฌธ์€ 2๋‹จ๊ณ„ ๊ธธ๋กœํ‹ด ์ ˆ๋‹จ(two-staged guillotine cut)์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด์œค์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” 2์ฐจ์› 2๋‹จ๊ณ„ ๋ฐฐ๋‚ญ ๋ฌธ์ œ(two-dimensional two-staged knapsack problem: ์ดํ•˜ 2TDK)์— ๋Œ€ํ•œ ์ •์ˆ˜์ตœ์ ํ™” ๋ชจํ˜•๊ณผ ์ตœ์ ํ•ด๋ฒ•์„ ๋‹ค๋ฃฌ๋‹ค. ์šฐ์„ , ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ŠคํŠธ๋ฆฝํŒจํ‚น๋ชจํ˜•, ๋‹จ๊ณ„ํŒจํ„ด๋ชจํ˜•, ๋ ˆ๋ฒจํŒจํ‚น๋ชจํ˜•, ๊ทธ๋ฆฌ๊ณ  ํ˜ธ-ํ๋ฆ„๋ชจํ˜•๊ณผ ๊ฐ™์€ ์ •์ˆ˜์ตœ์ ํ™” ๋ชจํ˜•๋“ค์„ ์†Œ๊ฐœํ•œ๋‹ค. ๊ทธ ๋’ค, ๊ฐ๊ฐ์˜ ๋ชจํ˜•์˜ ์„ ํ˜•๊ณ„ํš์™„ํ™”๋ฌธ์ œ์— ๋Œ€ํ•ด ์ƒํ•œ๊ฐ•๋„๋ฅผ ์ด๋ก ์ ์œผ๋กœ ๋ถ„์„ํ•˜์—ฌ ์ƒํ•œ๊ฐ•๋„ ๊ด€์ ์—์„œ ๋ชจํ˜•๋“ค ๊ฐ„ ์œ„๊ณ„๋ฅผ ์ •๋ฆฝํ•œ๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 2TDK์˜ ๋‹คํ•ญํฌ๊ธฐ(polynomial-size) ๋ชจํ˜•์˜ ์กด์žฌ์„ฑ์„ ์ฒ˜์Œ์œผ๋กœ ์ฆ๋ช…ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ๋Š” 2TDK์˜ ์ตœ์ ํ•ด๋ฅผ ๊ตฌํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ์จ ํŒจํ„ด๊ธฐ๋ฐ˜๋ชจํ˜•๋“ค์— ๋Œ€ํ•œ ๋ถ„์ง€ํ‰๊ฐ€ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ๋ ˆ๋ฒจํŒจํ‚น๋ชจํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋ถ„์ง€์ ˆ๋‹จ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹จ๊ณ„ํŒจํ„ด๋ชจํ˜•์ด ์ด๋ก ์ ์œผ๋กœ๋„ ๊ฐ€์žฅ ์ข‹์€ ์ƒํ•œ๊ฐ•๋„๋ฅผ ๋ณด์žฅํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ๊ณ„์‚ฐ ๋ถ„์„์„ ํ†ตํ•ด ๋‹จ๊ณ„ํŒจํ„ด๋ชจํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋ถ„์ง€ํ‰๊ฐ€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ œํ•œ๋œ ์‹œ๊ฐ„ ๋‚ด ์ข‹์€ ํ’ˆ์งˆ์˜ ๊ฐ€๋Šฅํ•ด๋ฅผ ์ฐพ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค.Abstract i Contents iv List of Tables vi List of Figures vii Chapter 1 Introduction 1 1.1 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . 8 Chapter 2 Integer Programming Models for 2TDK 9 2.1 Pattern-based Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Arc-flow Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.3 Level Packing Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 3 Theoretical Analysis of Integer Programming Models 20 3.1 Upper Bounds of AF and SM(1;1) . . . . . . . . . . . . . . . . . . 20 3.2 Upper Bounds of ML, PM(d), and SM(d; d) . . . . . . . . . . . . . . 21 3.3 Polynomial-size Model . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Chapter 4 Exact Methods 33 4.1 Branch-and-price Algorithm for the Strip Packing Model . . . . . . . 34 4.2 Branch-and-price Algorithm for the Staged-pattern Model . . . . . . 39 4.2.1 The Standard Scheme . . . . . . . . . . . . . . . . . . . . . . 39 4.2.2 The Height-aggregated Scheme . . . . . . . . . . . . . . . . . 40 4.3 Branch-and-cut Algorithm for the Modified Level Packing Model . . 44 Chapter 5 Computational Experiments 46 5.1 Instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.2 Upper Bounds Comparison . . . . . . . . . . . . . . . . . . . . . . . 49 5.2.1 A Group of Small Instances . . . . . . . . . . . . . . . . . . . 49 5.2.2 A Group of Large Instances . . . . . . . . . . . . . . . . . . . 55 5.2.3 Class 5 Instances . . . . . . . . . . . . . . . . . . . . . . . . . 61 5.3 Solving Instances to Optimality . . . . . . . . . . . . . . . . . . . . . 65 5.3.1 A Group of Small Instances . . . . . . . . . . . . . . . . . . . 65 5.3.2 A Group of Large Instances . . . . . . . . . . . . . . . . . . . 69 5.3.3 Class 5 Instances . . . . . . . . . . . . . . . . . . . . . . . . . 72 Chapter 6 Conclusion 77 Bibliography 79 ๊ตญ๋ฌธ์ดˆ๋ก 83Maste

    Finding Resources for Health Reform and Bending the Health Care Cost Curve

    Get PDF
    Examines policy options for slowing healthcare spending growth, improving outcomes, and financing comprehensive reform, including changes to Medicare Advantage and hospital pay-for-performance. Compares their estimated budget impact over ten years

    Algorithms for two-dimensional guillotine packing problems

    Get PDF
    The Guillotine Two-Dimensional Packing Problems are a class of optimization problems that require to pack rectangular items into rectangular containers with the constraint that every packed item should be possibly retrieved with a series of vertical and horizontal cuts that divide the container into 2 parts without cutting items. 2 exact and 2 heuristic algorithms have been developed, to solve respectively the Guillotine Two-Dimensional Knapsack and the Guillotine Two-Dimensional Bin Packingope

    Models and Solutions of Resource Allocation Problems based on Integer Linear and Nonlinear Programming

    Get PDF
    In this thesis we deal with two problems of resource allocation solved through a Mixed-Integer Linear Programming approach and a Mixed-Integer Nonlinear Chance Constraint Programming approach. In the first part we propose a framework to model general guillotine restrictions in two dimensional cutting problems formulated as Mixed-Integer Linear Programs (MILP). The modeling framework requires a pseudo-polynomial number of variables and constraints, which can be effectively enumerated for medium-size instances. Our modeling of general guillotine cuts is the first one that, once it is implemented within a state of-the-art MIP solver, can tackle instances of challenging size. Our objective is to propose a way of modeling general guillotine cuts via Mixed Integer Linear Programs (MILP), i.e., we do not limit the number of stages (restriction (ii)), nor impose the cuts to be restricted (restriction (iii)). We only ask the cuts to be guillotine ones (restriction (i)). We mainly concentrate our analysis on the Guillotine Two Dimensional Knapsack Problem (G2KP), for which a model, and an exact procedure able to significantly improve the computational performance, are given. In the second part we present a Branch-and-Cut algorithm for a class of Nonlinear Chance Constrained Mathematical Optimization Problems with a finite number of scenarios. This class corresponds to the problems that can be reformulated as Deterministic Convex Mixed-Integer Nonlinear Programming problems, but the size of the reformulation is large and quickly becomes impractical as the number of scenarios grows. We apply the Branch-and-Cut algorithm to the Mid-Term Hydro Scheduling Problem, for which we propose a chance-constrained formulation. A computational study using data from ten hydro plants in Greece shows that the proposed methodology solves instances orders of magnitude faster than applying a general-purpose solver for Convex Mixed-Integer Nonlinear Problems to the deterministic reformulation, and scales much better with the number of scenarios

    Cultivating the Next Generation of Art Lovers: How Boston Lyric Opera Sought to Create Greater Opportunities for Families to Attend Opera

    Get PDF
    Examines the evolution, outcomes, and factors shaping BLO's efforts to expand its audience through high-quality productions of abridged operas for families, supplemented by free previews and workshops at community venues. Outlines lessons learned

    Decomposition, Reformulation, and Diving in University Course Timetabling

    Full text link
    In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition, also known as the Udine Course Timetabling Problem. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.Comment: 45 pages, 7 figures. Improved typesetting of figures and table

    Medical circumcision integrated within traditional male initiation ceremonies for HIV prevention in Yangoru-Saussia, Papua New Guinea

    Get PDF
    Clement Manineng investigated the acceptability and feasibility of integrating medical circumcision within male initiation ceremonies in Yangoru-Saussia, Papua new Guinea. The intervention was acceptable and feasible although there were tensions between cultural and biomedical practices. A culture-oriented model for comprehensive HIV prevention in Yangoru-Saussia is developed from these results
    • โ€ฆ
    corecore