International audienceLagrangian relaxation is usually considered in the combinatorial optimization community as a mere technique, sometimes useful to compute bounds. It is actually a very general method, inevitable as soon as one bounds optimal values, relaxes constraints, convexifies sets, generates columns, etc. In this paper we review this method, from both points of view of theory (to dualize a given problem) and algorithms (to solve the dual by nonsmooth optimization)
Relaxation and dual-based heuristics have been a part of research in combinatorial optimisation sinc...
Operations in areas of importance to society are frequently modeled as Mixed-Integer Linear Programm...
International audienceWe consider the general polynomial optimization problem $P: f^*=\min \{f(x)\,:...
International audienceLagrangian relaxation is usually considered in the combinatorial optimization ...
It is well-known that the Lagrangian dual of an Integer Linear Program (ILP) provides the same bound...
Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a ...
AbstractWe consider the problem of maximizing a general pseudo-Boolean function. We formulate the pr...
We show that various duals that occur in optimization and constraint satisfaction can be classified ...
In mathematical optimzation, the Lagrangian approach is a general method to find an optimal solution...
This paper studies how to generalize Lagrangian relaxation to high-level optimization models, includ...
134 pagesNonconvex optimizations are ubiquitous in many application fields. One important aspect of ...
• Main purpose of my talk is “an introduction to the recent development of SDP relaxation in connect...
"April 10, 1991."Includes bibliographical references (p. 26-29).Research supported by the National S...
We revisit the classic supporting hyperplane illustration of the duality gap for non-convex optimiza...
We propose a general dual program for a constrained optimization problem via generalized nonlinear L...
Relaxation and dual-based heuristics have been a part of research in combinatorial optimisation sinc...
Operations in areas of importance to society are frequently modeled as Mixed-Integer Linear Programm...
International audienceWe consider the general polynomial optimization problem $P: f^*=\min \{f(x)\,:...
International audienceLagrangian relaxation is usually considered in the combinatorial optimization ...
It is well-known that the Lagrangian dual of an Integer Linear Program (ILP) provides the same bound...
Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a ...
AbstractWe consider the problem of maximizing a general pseudo-Boolean function. We formulate the pr...
We show that various duals that occur in optimization and constraint satisfaction can be classified ...
In mathematical optimzation, the Lagrangian approach is a general method to find an optimal solution...
This paper studies how to generalize Lagrangian relaxation to high-level optimization models, includ...
134 pagesNonconvex optimizations are ubiquitous in many application fields. One important aspect of ...
• Main purpose of my talk is “an introduction to the recent development of SDP relaxation in connect...
"April 10, 1991."Includes bibliographical references (p. 26-29).Research supported by the National S...
We revisit the classic supporting hyperplane illustration of the duality gap for non-convex optimiza...
We propose a general dual program for a constrained optimization problem via generalized nonlinear L...
Relaxation and dual-based heuristics have been a part of research in combinatorial optimisation sinc...
Operations in areas of importance to society are frequently modeled as Mixed-Integer Linear Programm...
International audienceWe consider the general polynomial optimization problem $P: f^*=\min \{f(x)\,:...