Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...
Heuristics are an increasingly popular solution method for combinatorial optimization problems. Heuristic use often frees the modeler from some of the restrictions placed on class...
Often, an outcome must be chosen on the basis of the preferences reported by a group of agents. The key difficulty is that the agents may report their preferences insincerely to m...
The design of effective neighborhood structures is fundamentally important for creating better local search and metaheuristic algorithms for combinatorial optimization. Significant...
We analyze the performance of evolutionary algorithms on various matroid optimization problems that encompass a vast number of efficiently solvable as well as NP-hard combinatoria...