In this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserabl...
— Cross protocol layer optimizations have been recently proposed for improving the performance of realtime video transmission over 802.11 WLANs. However, performing such cross-la...
Raymond S. Wong, Mihaela van der Schaar, Deepak S....
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
Abstract- The Pareto optimal solutions to a multiobjective optimization problem often distribute very regularly in both the decision space and the objective space. Most existing ev...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Edward P. K....
Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to well established stochastic heuristics such as SA, TS and GA, with shorter runti...
Approximate symbolic computation problems can be formulated as constrained or unconstrained optimization problems, for example: GCD [3, 8, 12, 13, 23], factorization [5, 10], and ...
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...
This contribution is the first to discover exploitable structural features within circuit optimization problems (COP) and discuss how it is indicative of a general structure and ...
When facing dynamic optimization problems the goal is no longer to find the extrema, but to track their progression through the space as closely as possible. Over these kind of ov...
Carlos Fernandes, Agostinho C. Rosa, Vitorino Ramo...