We consider incremental combinatorial optimization problems, in which a solution is constructed incrementally over time, and the goal is to optimize not the value of the final solution but the average value over all timesteps. We consider a natural algorithm of moving towards a global optimum solution as quickly as possible. We show that this algorithm provides an approximation guarantee of (9 + √21)/15 > 0.9 for a large class of incremental combinatorial optimization problems defined axiomatically, which includes (bipartite and non-bipartite) matchings, matroid intersections, and stable sets in claw-free graphs. Furthermore, our analysis is tight
Standard local search algorithms for combinatorial optimization problems repeatedly apply small chan...
This paper is motivated by the fact that many systems need to be maintained continually while the un...
Solution techniques for combinatorial optimization and integer programming problems are core discipl...
We consider incremental combinatorial optimization problems, in which a solution is constructed incr...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2018Cataloged from...
Many combinatorial optimization problems aim to select a subset of elements of maximum value subjec...
We propose a theoretical framework to capture incremental solutions to cardinality constrained maxim...
Traditional optimization algorithms are concerned with static input, static constraints, and attemp...
Typical optimization problems aim to select a single solution of maximum or minimum value from a lar...
The robustness function of an optimization problem measures the maximum change in the value of its o...
AbstractPerhaps the best known algorithm in combinatorial optimization is the greedy algorithm. A na...
In the early 1980s, Kirkpatrick et al. [1] and, independently, Černý [2] introduced simulated anneal...
The robustness function of an optimization problem measures the maximum change in the value of its o...
In this paper, we present a general framework for designing approximation schemes for combinatorial ...
Caption title.Includes bibliographical references (p. 19).Supported by a grant from NSF. DMI-9625489...
Standard local search algorithms for combinatorial optimization problems repeatedly apply small chan...
This paper is motivated by the fact that many systems need to be maintained continually while the un...
Solution techniques for combinatorial optimization and integer programming problems are core discipl...
We consider incremental combinatorial optimization problems, in which a solution is constructed incr...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2018Cataloged from...
Many combinatorial optimization problems aim to select a subset of elements of maximum value subjec...
We propose a theoretical framework to capture incremental solutions to cardinality constrained maxim...
Traditional optimization algorithms are concerned with static input, static constraints, and attemp...
Typical optimization problems aim to select a single solution of maximum or minimum value from a lar...
The robustness function of an optimization problem measures the maximum change in the value of its o...
AbstractPerhaps the best known algorithm in combinatorial optimization is the greedy algorithm. A na...
In the early 1980s, Kirkpatrick et al. [1] and, independently, Černý [2] introduced simulated anneal...
The robustness function of an optimization problem measures the maximum change in the value of its o...
In this paper, we present a general framework for designing approximation schemes for combinatorial ...
Caption title.Includes bibliographical references (p. 19).Supported by a grant from NSF. DMI-9625489...
Standard local search algorithms for combinatorial optimization problems repeatedly apply small chan...
This paper is motivated by the fact that many systems need to be maintained continually while the un...
Solution techniques for combinatorial optimization and integer programming problems are core discipl...