Zobrazeno 1 - 10
of 145
pro vyhledávání: '"Hooker, J. N."'
Statistical parity metrics have been widely studied and endorsed in the AI community as a means of achieving fairness, but they suffer from at least two weaknesses. They disregard the actual welfare consequences of decisions and may therefore fail to
Externí odkaz:
http://arxiv.org/abs/2405.11421
Geographical considerations such as contiguity and compactness are necessary elements of political districting in practice. Yet an analysis of the problem without such constraints yields mathematical insights that can inform real-world model construc
Externí odkaz:
http://arxiv.org/abs/2108.06381
Autor:
Chen, Violet Xinying, Hooker, J. N.
We propose social welfare optimization as a general paradigm for formalizing fairness in AI systems. We argue that optimization models allow formulation of a wide range of fairness criteria as social welfare functions, while enabling AI to take advan
Externí odkaz:
http://arxiv.org/abs/2102.00311
Autor:
Elci, Ozgun, Hooker, J. N.
We apply logic-based Benders decomposition (LBBD) to two-stage stochastic planning and scheduling problems in which the second-stage is a scheduling task. We solve the master problem with mixed integer/linear programming and the subproblem with const
Externí odkaz:
http://arxiv.org/abs/2012.14074
Autor:
Chen, Violet Xinying, Hooker, J. N.
Optimization models generally aim for efficiency by maximizing total benefit or minimizing cost. Yet a trade-off between fairness and efficiency is an important element of many practical decisions. We propose a principled and practical method for bal
Externí odkaz:
http://arxiv.org/abs/2006.05963
Autor:
Hooker, J. N.
Logic-based Benders decomposition (LBBD) is a substantial generalization of classical Benders decomposition that, in principle, allows the subproblem to be any optimization problem rather than specifically a linear or nonlinear programming problem. I
Externí odkaz:
http://arxiv.org/abs/1910.11944
Autor:
Benade, J. G., Hooker, J. N.
Publikováno v:
INFORMS Journal on Computing, published online 19 July 2019
We present a general method for obtaining strong bounds for discrete optimization problems that is based on a concept of branching duality. It can be applied when no useful integer programming model is available, and we illustrate this with the minim
Externí odkaz:
http://arxiv.org/abs/1908.07584
Autor:
Hooker, J. N.
We introduce a general method for relaxing decision diagrams that allows one to bound job sequencing problems by solving a Lagrangian dual problem on a relaxed diagram. We also provide guidelines for identifying problems for which this approach can r
Externí odkaz:
http://arxiv.org/abs/1908.07076
Autor:
Genc-Kaya, Latife, Hooker, J. N.
The hamiltonian circuit polytope is the convex hull of feasible solutions for the circuit constraint, which provides a succinct formulation of the traveling salesman and other sequencing problems. We study the polytope by establishing its dimension,
Externí odkaz:
http://arxiv.org/abs/1812.02235
Autor:
Davarnia, Danial, Hooker, J. N.
Concepts of consistency have long played a key role in constraint programming but never developed in integer programming (IP). Consistency nonetheless plays a role in IP as well. For example, cutting planes can reduce backtracking by achieving variou
Externí odkaz:
http://arxiv.org/abs/1812.02215