A Restricted Dual Peaceman-Rachford Splitting Method for a Strengthened DNN Relaxation for QAP
From MaRDI portal
Publication:5106411
DOI10.1287/ijoc.2022.1161OpenAlexW4220679245MaRDI QIDQ5106411
Naomi Graham, Hao Hu, Henry Wolkowicz, Xinxin Li, Jiyoung Im
Publication date: 19 September 2022
Published in: INFORMS Journal on Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1287/ijoc.2022.1161
quadratic assignment problemsemidefinite relaxationdoubly nonnegative relaxationfacial reductionpeaceman-Rachford splitting method
Related Items
Uses Software
Cites Work
- SPGL1
- SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints
- QAPLIB-A quadratic assignment problem library
- Copositive and semidefinite relaxations of the quadratic assignment problem
- Bounds for the quadratic assignment problem using the bundle method
- Semidefinite programming relaxations for the quadratic assignment problem
- ADMM for the SDP relaxation of the QAP
- Semidefinite programming approach for the quadratic assignment problem with a sparse graph
- Relaxed inertial proximal Peaceman-Rachford splitting method for separable convex programming
- A strictly contractive Peaceman-Rachford splitting method for the doubly nonnegative relaxation of the minimum cut problem
- On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
- On the global and linear convergence of the generalized alternating direction method of multipliers
- Linear Convergence of the Alternating Direction Method of Multipliers for a Class of Convex Optimization Problems
- A New Genetic Algorithm for the Quadratic Assignment Problem
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- A Strictly Contractive Peaceman--Rachford Splitting Method for Convex Programming
- Exact solution of emerging quadratic assignment problems
- Ant colonies for the quadratic assignment problem
- Partial Error Bound Conditions and the Linear Convergence Rate of the Alternating Direction Method of Multipliers
- A Proximal Strictly Contractive Peaceman--Rachford Splitting Method for Convex Programming with Applications to Imaging
- Probing the Pareto Frontier for Basis Pursuit Solutions
- Scheduling Parallel Production Lines with Changeover Costs: Practical Application of a Quadratic Assignment/LP Approach
- Hospital Layout as a Quadratic Assignment Problem
- Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
- Level 2 Reformulation Linearization Technique–Based Parallel Algorithms for Solving Large Quadratic Assignment Problems on Graphics Processing Unit Clusters
- Linear Rate Convergence of the Alternating Direction Method of Multipliers for Convex Composite Programming
- Iteration-Complexity of Block-Decomposition Algorithms and the Alternating Direction Method of Multipliers
- Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions
- Local Linear Convergence of the Alternating Direction Method of Multipliers for Quadratic Programs
- Local Linear Convergence of the Alternating Direction Method of Multipliers on Quadratic or Linear Programs
- The Distribution of Values in the Quadratic Assignment Problem
- Handbook of semidefinite programming. Theory, algorithms, and applications
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
