1,126 research outputs found
Robust capacitated trees and networks with uniform demands
We are interested in the design of robust (or resilient) capacitated rooted
Steiner networks in case of terminals with uniform demands. Formally, we are
given a graph, capacity and cost functions on the edges, a root, a subset of
nodes called terminals, and a bound k on the number of edge failures. We first
study the problem where k = 1 and the network that we want to design must be a
tree covering the root and the terminals: we give complexity results and
propose models to optimize both the cost of the tree and the number of
terminals disconnected from the root in the worst case of an edge failure,
while respecting the capacity constraints on the edges. Second, we consider the
problem of computing a minimum-cost survivable network, i.e., a network that
covers the root and terminals even after the removal of any k edges, while
still respecting the capacity constraints on the edges. We also consider the
possibility of protecting a given number of edges. We propose three different
formulations: a cut-set based formulation, a flow based one, and a bilevel one
(with an attacker and a defender). We propose algorithms to solve each
formulation and compare their efficiency
Contingency-Constrained Unit Commitment With Intervening Time for System Adjustments
The N-1-1 contingency criterion considers the con- secutive loss of two
components in a power system, with intervening time for system adjustments. In
this paper, we consider the problem of optimizing generation unit commitment
(UC) while ensuring N-1-1 security. Due to the coupling of time periods
associated with consecutive component losses, the resulting problem is a very
large-scale mixed-integer linear optimization model. For efficient solution, we
introduce a novel branch-and-cut algorithm using a temporally decomposed
bilevel separation oracle. The model and algorithm are assessed using multiple
IEEE test systems, and a comprehensive analysis is performed to compare system
performances across different contingency criteria. Computational results
demonstrate the value of considering intervening time for system adjustments in
terms of total cost and system robustness.Comment: 8 pages, 5 figure
A New General-Purpose Algorithm for Mixed-Integer Bilevel Linear Programs
Bilevel optimization problems are very challenging optimization models arising in many important practical contexts, including pricing mechanisms in the energy sector, airline and telecommunication industry, transportation networks, critical infrastructure defense, and machine learning. In this paper, we consider bilevel programs with continuous and discrete variables at both levels, with linear objectives and constraints (continuous upper level variables, if any, must not appear in the lower level problem). We propose a general-purpose branch-and-cut exact solution method based on several new classes of valid inequalities, which also exploits a very effective bilevel-specific preprocessing procedure. An extensive computational study is presented to evaluate the performance of various solution methods on a common testbed of more than 800 instances from the literature and 60 randomly generated instances. Our new algorithm consistently outperforms (often by a large margin) alternative state-of-the-art methods from the literature, including methods exploiting problem-specific information for special instance classes. In particular, it solves to optimality more than 300 previously unsolved instances from the literature. To foster research on this challenging topic, our solver is made publicly available online
On SOCP-based disjunctive cuts for solving a class of integer bilevel nonlinear programs
We study a class of integer bilevel programs with second-order cone
constraints at the upper-level and a convex-quadratic objective function and
linear constraints at the lower-level. We develop disjunctive cuts (DCs) to
separate bilevel-infeasible solutions using a second-order-cone-based
cut-generating procedure. We propose DC separation strategies and consider
several approaches for removing redundant disjunctions and normalization. Using
these DCs, we propose a branch-and-cut algorithm for the problem class we
study, and a cutting-plane method for the problem variant with only binary
variables.
We present an extensive computational study on a diverse set of instances,
including instances with binary and with integer variables, and instances with
a single and with multiple linking constraints. Our computational study
demonstrates that the proposed enhancements of our solution approaches are
effective for improving the performance. Moreover, both of our approaches
outperform a state-of-the-art generic solver for mixed-integer bilevel linear
programs that is able to solve a linearized version of our binary instances.Comment: arXiv admin note: substantial text overlap with arXiv:2111.0682
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