In column generation schemes, particularly those proposed for set partitioning type problems, dynamic programming algorithms are applied to solve the respective pricing subproblem. In addition to traditional dominance criteria for state space reduction, we develop a simple generic lower bounding criterion based on the dual optimal solution of the restricted master problem. Key words: Dynamic programming; Column generation; Linear programming Column generation is a prominent---and often the solely applicable---method to cope with linear programming problems with a colossal number of variables. In recent years we have been witnessing the optimal solution of truly large problems, but still the need for faster algorithms remains, especially in ...
Working in an extended variable space allows one to develop tighter reformu- lations for mixed integ...
This paper shows how branch-and-bound methods can be used to reduce storage and, possibly, computati...
AbstractColumn generation algorithms are instrumental in many areas of applied optimization, where l...
In this note, we aim at reducing the state space of dynamic programming algorithms used as column ge...
We describe a new approach to produce integer feasible columns to a set partitioning problem directl...
Column generation is a linear programming method that, when combined with appropriate integer progra...
We discuss formulations of integer programs with a huge number of variables and their solution by co...
Column generation is a linear programming method in which a dual solution of the master problem is e...
informs ® doi 10.1287/opre.1050.0234 © 2005 INFORMS Dantzig-Wolfe decomposition and column generatio...
Column generation is a well-known and widely practiced technique for solving linear programs with to...
Column generation is a well-known and widely practiced technique for solving linear programs with to...
Solving large scale nonlinear optimization problems requires either significant computing resource...
Column generation algorithms have been specially designed for solving mathemat-ical programs with a ...
Column generation algorithms are instrumental in many areas of applied optimization, where linear pr...
Some Mixed Integer Programs (MTP's) have many more rows than columns. Because the time taken to solv...
Working in an extended variable space allows one to develop tighter reformu- lations for mixed integ...
This paper shows how branch-and-bound methods can be used to reduce storage and, possibly, computati...
AbstractColumn generation algorithms are instrumental in many areas of applied optimization, where l...
In this note, we aim at reducing the state space of dynamic programming algorithms used as column ge...
We describe a new approach to produce integer feasible columns to a set partitioning problem directl...
Column generation is a linear programming method that, when combined with appropriate integer progra...
We discuss formulations of integer programs with a huge number of variables and their solution by co...
Column generation is a linear programming method in which a dual solution of the master problem is e...
informs ® doi 10.1287/opre.1050.0234 © 2005 INFORMS Dantzig-Wolfe decomposition and column generatio...
Column generation is a well-known and widely practiced technique for solving linear programs with to...
Column generation is a well-known and widely practiced technique for solving linear programs with to...
Solving large scale nonlinear optimization problems requires either significant computing resource...
Column generation algorithms have been specially designed for solving mathemat-ical programs with a ...
Column generation algorithms are instrumental in many areas of applied optimization, where linear pr...
Some Mixed Integer Programs (MTP's) have many more rows than columns. Because the time taken to solv...
Working in an extended variable space allows one to develop tighter reformu- lations for mixed integ...
This paper shows how branch-and-bound methods can be used to reduce storage and, possibly, computati...
AbstractColumn generation algorithms are instrumental in many areas of applied optimization, where l...