A truncated descent HS conjugate gradient method and its global convergence.
A trust region method for zero-one nonlinear programming
A Trust Region Method Using Subgradient for Minimizing a Nondifferentiable Function
A trust-region-based BFGS method with line search technique for symmetric nonlinear equations.
A Two-Phase Linear Programming Approach for Redundancy Allocation Problems
A two-stage stochastic optimization model for a gas sale retailer
The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization Modelling for Gas Seller–Stochastic Version), to assist companies dealing with gas retail commercialization. Stochasticity is due to the dependence of consumptions on temperature uncertainty. Due to nonlinearities present in the objective function, the model can be classified as an NLP mixed integer model, with the profit function depending on the number of contracts with the final consumers, the typology of...
A unified characterization of -optimal and minimal entropy martingale measures by semimartingale backward equations.
A vanishing discount limit theorem for controlled Markov chains
A Variable Metric Algorithm for Unconstrained Minimization Without Evaluation of Derivatives.
A variational model for urban planning with traffic congestion
We propose a variational model to describe the optimal distributions of residents and services in an urban area. The functional to be minimized involves an overall transportation cost taking into account congestion effects and two aditional terms which penalize concentration of residents and dispersion of services. We study regularity properties of the minimizers and treat in details some examples.
A variational model for urban planning with traffic congestion
We propose a variational model to describe the optimal distributions of residents and services in an urban area. The functional to be minimized involves an overall transportation cost taking into account congestion effects and two aditional terms which penalize concentration of residents and dispersion of services. We study regularity properties of the minimizers and treat in details some examples.
A View of Interior Point Methods for Linear Programming
A viewpoint to the minimum coloring problem of hypergraphs
A weighted analytic center for linear matrix inequalities.
About a special class of nonconvex optimization problems
The article deals with certain nonconvex optimization problem which have features analogous to those of the linear optimization problems. We can find their absolute extrema and the set all optimal points of such nonconvex optimization problem represents the closure of a face of a spherical polyhedron which is its feasible set.
About an inequality of Kubota for plane convex figures.
About Some Problems of Disjunctive Programming
About stability of risk-seeking optimal stopping
We offer the quantitative estimation of stability of risk-sensitive cost optimization in the problem of optimal stopping of Markov chain on a Borel space . It is supposed that the transition probability , is approximated by the transition probability , , and that the stopping rule , which is optimal for the process with the transition probability is applied to the process with the transition probability . We give an upper bound (expressed in term of the total variation distance: for...
About the choice of the variable to unassign in a decision repair algorithm
The decision repair algorithm (Jussien and Lhomme, Artificial Intelligence 139 (2002) 21–45), which has been designed to solve constraint satisfaction problems (CSP), can be seen, either (i) as an extension of the classical depth first tree search algorithm with the introduction of a free choice of the variable to which to backtrack in case of inconsistency, or (ii) as a local search algorithm in the space of the partial consistent variable assignments. or (iii) as a hybridisation between local...
About the choice of the variable to unassign in a decision repair algorithm
The decision repair algorithm (Jussien and Lhomme, Artificial Intelligence139 (2002) 21–45), which has been designed to solve constraint satisfaction problems (CSP), can be seen, either (i) as an extension of the classical depth first tree search algorithm with the introduction of a free choice of the variable to which to backtrack in case of inconsistency, or (ii) as a local search algorithm in the space of the partial consistent variable assignments. or (iii) as a hybridisation between local...