Exact Solution of Graph Coloring Problems via Constraint Programming and Column Generation

We consider two approaches for solving the classical minimum vertex coloring problem�that is, the problem of coloring the vertices of a graph so that adjacent vertices have different colors and minimizing the number of used colors, namely, constraint programming and column generation. Constraint programming is able to solve very efficiently many of the benchmarks but … Read more

Exactly solving a Two-level Hierarchical Location Problem with modular node capacities

In many telecommunication networks a given set of client nodes must be served by different sets of facilities, providing different services and having different capabilities, which must be located and dimensioned in the design phase. Network topology must be designed as well, by assigning clients to facilities and facilities to higher level entities, when necessary. … Read more

Modeling and Solving Location Routing and Scheduling Problems

This paper studies location routing and scheduling problems, a class of problems in which the decisions of facility location, vehicle routing, and route assignment are optimized simultaneously. For a version with capacity and time restrictions, two formulations are presented, one graph-based and one set-partitioning-based. For the set-partitioning-based formulation, valid inequalities are identified and their effectiveness … Read more

Algorithms over Arc-time Indexed Formulations for Single and Parallel Machine Scheduling Problems

This paper presents algorithms for single and parallel identical machine scheduling problems. While the overall algorithm can be viewed as a branch-cut-and-price over a very large extended formulation, a number of auxiliary techniques are necessary to make the column generation effective. Those techniques include a powerful fixing by reduced costs and a new proposed dual … Read more

A Branch-and-Price Algorithm for Combined Location and Routing Problems Under Capacity Restrictions

We investigate the problem of simultaneously determining the location of facilities and the design of vehicle routes to serve customer demands under vehicle and facility capacity restrictions. We present a set-partitioning-based formulation of the problem and study the relationship between his formulation and the graph-based formulations that have been used in previous studies of this … Read more

A conjugate-gradient based approach for approximate solutions of quadratic programs

This paper deals with numerical behaviour and convergence properties of a recently presented column generation approach for optimization of so called step-and-shoot radiotherapy treatment plans. The approach and variants of it have been reported to be efficient in practice, finding near-optimal solutions by generating only a low number of columns. The impact of different restrictions … Read more

Adaptive Constraint Reduction for Convex Quadratic Programming

We propose an adaptive, constraint-reduced, primal-dual interior-point algorithm for convex quadratic programming with many more inequality constraints than variables. We reduce the computational e ort by assembling, instead of the exact normal-equation matrix, an approximate matrix from a well chosen index set which includes indices of constraints that seem to be most critical. Starting with a … Read more

Adaptive Constraint Reduction for Training Support Vector Machines

A support vector machine (SVM) determines whether a given observed pattern lies in a particular class. The decision is based on prior training of the SVM on a set of patterns with known classification, and training is achieved by solving a convex quadratic programming problem. Since there are typically a large number of training patterns, … Read more

Combining segment generation with direct step-and-shoot optimization in intensity-modulated radiation therapy

A method for generating a sequence of intensity-modulated radiation therapy step-and-shoot plans with increasing number of segments is presented. The objectives are to generate high-quality plans with few, large and regular segments, and to make the planning process more intuitive. The proposed method combines segment generation with direct step-and-shoot optimization, where leaf positions and segment … Read more

Selective Gram-Schmidt orthonormalization for conic cutting surface algorithms

It is not straightforward to find a new feasible solution when several conic constraints are added to a conic optimization problem. Examples of conic constraints include semidefinite constraints and second order cone constraints. In this paper, a method to slightly modify the constraints is proposed. Because of this modification, a simple procedure to generate strictly … Read more