Now showing items 1-6 of 6
Escaping local optima in a class of multi-agent distributed optimization problems: a boosting function approach
We address the problem of multiple local optima commonly arising in optimization problems for multi-agent systems, where objective functions are nonlinear and nonconvex. For the class of coverage control problems, we propose ...
Expected gain-loss pricing and hedging of contingent claims in incomplete markets by linear programming
We analyze the problem of pricing and hedging contingent claims in the multi-period, discrete time, discrete state case using the concept of a "λ gain-loss ratio opportunity". Pricing results somewhat different from, but ...
Generalized column generation for linear programming
(Institute for Operations Research and the Management Sciences (INFORMS), 2002)
Column generation is a well-known and widely practiced technique for solving linear programs with too many variables or constraints to include in the initial formulation explicitly. Instead, the required column information ...
A derivation of Lovász' theta via augmented lagrange duality
(E D P Sciences, 2003)
A recently introduced dualization technique for binary linear programs with equality constraints, essentially due to Poljak et al. , and further developed in Lemar´echal and Oustry , leads to simple alternative ...
A parametric simplex algorithm for linear vector optimization problems
In this paper, a parametric simplex algorithm for solving linear vector optimization problems (LVOPs) is presented. This algorithm can be seen as a variant of the multi-objective simplex (the Evans–Steuer) algorithm (Math ...
Discrete-time pricing and optimal exercise of American perpetual warrants in the geometric random walk model
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option ...