438 research outputs found
Odd-Cycle Separation for Maximum Cut and Binary Quadratic Optimization
Solving the NP-hard Maximum Cut or Binary Quadratic Optimization Problem to optimality is important in many applications including Physics, Chemistry, Neuroscience, and Circuit Layout. The leading approaches based on linear/semidefinite programming require the separation of so-called odd-cycle inequalities for solving relaxations within their associated branch-and-cut frameworks. In their groundbreaking work, F. Barahona and A.R. Mahjoub have given an informal description of a polynomial-time separation procedure for the odd-cycle inequalities. Since then, the odd-cycle separation problem has broadly been considered solved. However, as we reveal, a straightforward implementation is likely to generate inequalities that are not facet-defining and have further undesired properties. Here, we present a more detailed analysis, along with enhancements to overcome the associated issues efficiently. In a corresponding experimental study, it turns out that these are worthwhile, and may speed up the solution process significantly
A Strategic Approach to Building Affordable Housing in Philadelphia
Calls on the city to coordinate affordable housing production subsidies with other public and private investments in order to build sustainable mixed-income neighborhoods with energy-efficient homes, ensuring economic growth and long-term affordability
Economic and social impact of introducing casino gambling: a review and assessment of the literature
Reviews and assesses the existing literature on the potential economic impact of introducing casino gambling into a community or region, first by discussing the casinos? effect on economic activity and growth within a community or region, and then by exploring their effect on government revenues. Also discusses the literature related to the economic impact of social costs widely associated with gambling, such as increases in crime, bankruptcy, and problem gambling.Gambling industry
How to spend $3.92 billion: stabilizing neighborhoods by addressing foreclosed and abandoned properties
The Housing and Economic Recovery Act of 2008 created the Neighborhood Stabilization Program (NSP), under which states, cities, and counties will receive a total of $3.92 billion to acquire, rehabilitate, demolish, and redevelop foreclosed and abandoned residential properties. These funds can stabilize hard-hit neighborhoods, putting them on the path to market recovery. This will only happen, however, if they are used in ways that are strategically targeted and sensitive to market conditions. This paper outlines 11 key principles that states, counties, and cities should follow as they plan for and use NSP funds.Housing and Economic Recovery Act; Neighborhood Stabilization Program (NSP); Foreclosure
Challenges of the small rental property sector
Most rental housing in America is found in small multifamily buildings and this sector provides most of the options for low- and moderate-income (LMI) renters. With a growing wave of investors buying distressed properties in LMI neighborhoods, there are concerns about the ability of investors to properly maintain their investments. The author explores the small multifamily sector and suggests ways that policymakers can move beyond code enforcement and provide a combination of carrots and sticks to incentivize and increase the presence of “good actors."Rental housing
Home ownership education and counseling: issues in research and definition
Many public- and private-sector initiatives support the expansion of home-ownership opportunities for low- and moderate-income households. This discussion paper assesses existing research on the effectiveness of home-ownership education and counseling and opportunities for future research. A limited number of printed copies are available.Home ownership
Improved Mixed-Integer Programming Models for Multiprocessor Scheduling with Communication Delays
We revise existing and introduce new mixed-integer programming models for the Multiprocessor Scheduling Problem with Communication Delays. At first, we show how to provably reduce the number of product variables necessary to explicitly linearize the so-called packing formulation that contains bilinear terms. Then, we reveal that the feasible region of almost all existing formulations contains redundant solutions and formulate new constraints in order to exclude these. At the same time, by exploiting further structural properties, the models are improved concerning their size, strength, and modeling complexity. The discussion of these improvements leads to new much more compact formulations which are then experimentally compared with each other and with other formulations from the literature. We set up a realistic scenario with a preprocessing of the task graphs, delivering the gained information equally to all the tested models and evaluate not only running times but also the obtained lower and upper bounds on the makespan objective for unsolved instances of a large scale benchmark set
Compact Linearization for Binary Quadratic Problems Comprising Linear Constraints
In this paper, the compact linearization approach originally proposed for binary quadratic programs with assignment constraints is generalized to such programs with arbitrary linear equations and inequalities that have positive coefficients and right hand sides. Quadratic constraints may exist in addition, and the technique may as well be applied if these impose the only nonlinearities, i.e., the objective
function is linear. We present special cases of linear constraints (along with prominent combinatorial optimization problems where these occur) such that the associated compact linearization yields a linear programming relaxation that is provably as least as strong as the one obtained with a classical linearization method. Moreover, we show how to compute a compact linearization automatically which might
be used, e.g., by general-purpose mixed-integer programming solvers
Compact Hierarchical Graph Drawings via Quadratic Layer Assignment
We propose a new mixed-integer programming formulation that very naturally expresses the layout restrictions of a layered (hierarchical) graph drawing and several associated objectives, such as a minimum total arc length, number of reversed arcs, and width, or the adaptation to a specific drawing area, as a special quadratic assignment problem. Our experiments show that it is competitive to another formulation that we slightly simplify as well
The Tortured Reality of Suburban Exclusion: Zoning, Economics, and the Future of the Berenson Doctrine
- …