We study the estimation error of constrained M -estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the boundary of the constraint set (matched constraint), and where the true parameter is strictly in the constraint set (mismatched constraint) are considered. For bo...

We study a general multiobjective optimization problem with variational inequality, equality, inequality and abstract constraints. Fritz John type necessary optimality conditions involving Mordukhovich coderivatives are derived. They lead to Kuhn-Tucker type necessary optimality conditions under additional constraint qualifications including the calmness condition, the error bound constraint qu...

Optimization Problems Stephen Beale Computing Research Laboratory Box 30001 New Mexico State University Las Cruces, New Mexico 88003 [email protected] Abstract This work1 integrates three related AI search techniques { constraint satisfaction, branch-and-bound and solution synthesis { and applies the result to constraint satisfaction problems for which optimal answers are required. This method ha...

Branching and lower bounds are two key notions in heuristic search and combinatorial optimization. Branching refers to the way the space of solutions is searched, while lower bounds refer to approximate cost measures used for focusing and pruning the search. In AI Planning, admissible heuristics or lower bounds have received considerable attention and most current optimal planners use them, eit...

This paper discusses the complexity of bound consistency on n-ary linear constraint system and investigates the relationship between equivalent binary equation systems from the perspective of bound consistency techniques. We propose an efficient bound consistency enforcing algorithm whose complexity is .In addition, by transforming a binary equation system into solved form, an efficient consist...

MOTIVATION Computer-aided genetic design is a promising approach to a core problem of metabolic engineering-that of identifying genetic manipulation strategies that result in engineered strains with favorable product accumulation. This approach has proved to be effective for organisms including Escherichia coli and Saccharomyces cerevisiae, allowing for rapid, rational design of engineered stra...

Many problems in Artificial Intelligence, such as diagnosis, control, and planning, can be framed as constraint optimization problems where a limited number of leading solutions are needed. An important class of optimization algorithms use A*, a variant of best first search, to guide the search effectively, while employing a heuristic evaluation function that is computed using dynamic programmi...