Report of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Memorial Union Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Memorial Union Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Athletic Facilities Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Athletic Facilities Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Cigarette and Tobacco Receipts Report, September 2008

This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.

Iowa Department of Revenue Performance Plan, FY 2009

Agency Performance Plan, Iowa Department of Revenue

Iowa Workforce Development Revenue Performance Plan, FY 2009

Agency Performance Plan, Iowa Workforce Development

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Iowa Department of Revenue, Strategic Plan, 2007-2010

This report outlines the strategic plan for Iowa Department of Revenue, goals and mission.

Cigarette and Tobacco Receipts Report, October 2008

This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.

Tax simulation in the SHP

This paper describes a simulation package designed to estimate the annual income taxes paid by respondents of the Swiss Household Panel (SHP). In Switzerland, the 26 cantons have their own tax system. Additionally, tax levels vary between the over 2000 municipalities and over time. The simulation package takes account of this complexity by building on existing tables on tax levels which are provided by the Swiss Federal Tax Administration Office. Because these are limited to a few types of households and only 812 municipalities, they have to be extended to cover all households and municipalities. A further drawback of these tables is that they neglect several deductions. The tax simulation package fills this gap by taking additionally account of deductions for children, double-earner couples, third pillar and support for dependent persons according to cantonal legislation. The resulting variable on direct taxes not only serves to calculate household income net of taxes, but can also be a variable for analysis by its own account.

Cigarette and Tobacco Receipts Report, November 2008

This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.

Consumer Advisory Bulletin, Avoid Rapid Tax-Refund Loans December, 2008

The Attorney General’s Consumer Protection Division receives hundreds of calls and consumer complaints every year. Follow these tips to avoid unexpected expense and disappointments. This record is about: Avoid Rapid Tax-Refund Loans

Consumer Advisory Bulletin, Avoid Rapid Tax-Refund Loans December, 2008

The Attorney General’s Consumer Protection Division receives hundreds of calls and consumer complaints every year. Follow these tips to avoid unexpected expense and disappointments. This record is about: Avoid Rapid Tax-Refund Loans