BENDERS DECOMPOSITION METHOD

2011 ◽  
Keyword(s):  
Decomposition Method ◽  
Benders Decomposition

Efficient joint power and admission control in underlay cognitive networks using Benders’ decomposition method

2018 ◽  
Vol 129 ◽  
pp. 19-31 ◽  
Author(s):  
Fahime Khoramnejad ◽  
Mehdi Rasti ◽  
Hossein Pedram ◽  
Mehdi Monemi
Keyword(s):  
Admission Control ◽  
Decomposition Method ◽  
Benders Decomposition ◽  
Cognitive Networks ◽  
Joint Power

A modified Benders decomposition method for efficient robust optimization under interval uncertainty

2011 ◽  
Vol 44 (2) ◽  
pp. 259-275 ◽  
Author(s):  
Sauleh Siddiqui ◽  
Shapour Azarm ◽  
Steven Gabriel
Keyword(s):  
Robust Optimization ◽  
Decomposition Method ◽  
Benders Decomposition ◽  
Interval Uncertainty

Latest Advances on Benders Decomposition

2018 ◽  
pp. 5411-5421 ◽  
Author(s):  
Antonios Fragkogios ◽  
Georgios K. D. Saharidis
Keyword(s):  
Mathematical Programming ◽  
Operations Research ◽  
Decomposition Method ◽  
Large Scale ◽  
Benders Decomposition ◽  
Information Science ◽  
Solution Process ◽  
Cpu Time ◽  
Mathematical Problems ◽  
Modern Economic

Operations Research and Mathematical Programming together with Information Science and Technology are tools used to solve various problems in the modern economic environment. This chapter addresses the Benders Decomposition method, which is used for the solution of problems of Operations Research. This method, applied to certain large-scale mathematical problems, can make their solution feasible (if they cannot be solved with another procedure) or can accelerate the solution process in terms of CPU time. The authors provide a thorough presentation of how the decomposition of a problem is made and the Benders algorithm is applied for its solution. Main purpose of this chapter is to analyze the recent studies that address the method's weaknesses and accelerate its application for the faster solution of mathematical problems. A large number of papers is presented and the contribution of each one of them to the improvement of the method is described.

Optimization of the Operation Plan in the Porcelain Plant By the Benders Decomposition Method

1986 ◽  
Vol 19 (13) ◽  
pp. 403-406
Author(s):  
J. Kotowski ◽  
M. Sygit
Keyword(s):  
Decomposition Method ◽  
Benders Decomposition

The Benders Dual Decomposition Method

2020 ◽  
Vol 68 (3) ◽  
pp. 878-895
Author(s):  
Ragheb Rahmaniani ◽  
Shabbir Ahmed ◽  
Teodor Gabriel Crainic ◽  
Michel Gendreau ◽  
Walter Rei
Keyword(s):  
Decomposition Method ◽  
High Performance ◽  
Large Scale ◽  
Benders Decomposition ◽  
Master Problem ◽  
Computational Results ◽  
Dual Decomposition ◽  
High Quality ◽  
Lagrangian Dual ◽  
Decomposition Strategies

Many methods that have been proposed to solve large-scale MILP problems rely on the use of decomposition strategies. These methods exploit either the primal or dual structures of the problems by applying the Benders decomposition or Lagrangian dual decomposition strategy, respectively. In “The Benders Dual Decomposition Method,” Rahmaniani, Ahmed, Crainic, Gendreau, and Rei propose a new and high-performance approach that combines the complementary advantages of both strategies. The authors show that this method (i) generates stronger feasibility and optimality cuts compared with the classical Benders method, (ii) can converge to the optimal integer solution at the root node of the Benders master problem, and (iii) is capable of generating high-quality incumbent solutions at the early iterations of the algorithm. The developed algorithm obtains encouraging computational results when used to solve various benchmark MILP problems.

Active Distribution Network Optimal Power Flow Deploying the Benders Decomposition Method

2021 ◽  
Author(s):  
Mahan Fakouri Fard ◽  
Farhad Elyasichamazkoti ◽  
Armin Fooladi Savadkouhi
Keyword(s):  
Decomposition Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Benders Decomposition ◽  
Distribution Network ◽  
Active Distribution Network ◽  
Optimal Power
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