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New Branch-and-Bound Rules for Linear Bilevel Programming
A new branch-and-bound algorithm for linear bilevel programming is proposed. Necessary optimality conditions expressed in terms of tightness of the follower’s constraints are used to fathom or
Algorithms for the maximum satisfiability problem
TLDR
Two recent local search algorithmic schemes are considered, the Simulated Annealing method of Kirkpatrick, Gelatt and Vecchi and the Steepest Ascent Mildest Descent method, and adapt them to the Maximum Satisfiability problem and are shown empirically to be more efficient than the heuristics previously proposed in the literature.
Cluster analysis and mathematical programming
TLDR
Algorithms for hierarchical, partitioning, sequential, and additive clustering are studied, and emphasis is on solution methods, i.e., dynamic programming, graph theoretical algorithms, branch-and-bound, cutting planes, column generation and heuristics.
A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
TLDR
A branch and cut algorithm that yields in finite time, a globally ε-optimal solution (with respect to feasibility and optimality) of the nonconvex quadratically constrained quadratic programming problem.
On the Complexity of the Maximum Satisfiability Problem for Horn Formulas
Links Between Linear Bilevel and Mixed 0–1 Programming Problems
TLDR
It is shown that solving a linear mixed 0–1 problem by a classical branch-and-bound algorithm is equivalent in a strong sense to solving its bilevel reformulation by a bileVEL branch- and- bound algorithm.
An Interior Point Algorithm for Minimum Sum-of-Squares Clustering
An exact algorithm is proposed for minimum sum-of-squares nonhierarchical clustering, i.e., for partitioning a given set of points from a Euclidean m-space into a given number of clusters in order to
Physician Scheduling in Emergency Rooms
TLDR
Several possible solution techniques that can be applied to physician scheduling problems, namely tabu search, column generation, mathematical programming and constraint programming, are reviewed, and their suitability for application depending on the specifics of the situation at hand are examined.
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