Primal and Dual Decomposition as Organizational Design: Price and/or Resource Directive Decomposition

Author(s):  
Kaj Holmberg
2014 ◽  
Vol 33 ◽  
pp. 65-75
Author(s):  
HK Das ◽  
M Babul Hasan

In this paper, we study the methodology of primal dual solutions in Linear Programming (LP) & Linear Fractional Programming (LFP) problems. A comparative study is also made on different duals of LP & LFP. We then develop an improved decomposition approach for showing the relationship of primal and dual approach of LP & LFP problems by giving algorithm. Numerical examples are given to demonstrate our method. A computer programming code is also developed for showing primal and dual decomposition approach of LP & LFP with proper instructions using AMPL. Finally, we have drawn a conclusion stating the privilege of our method of computation. GANIT J. Bangladesh Math. Soc. Vol. 33 (2013) 65-75 DOI: http://dx.doi.org/10.3329/ganit.v33i0.17660


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
J. A. Marmolejo ◽  
R. Rodríguez ◽  
O. Cruz-Mejia ◽  
J. Saucedo

A method to solve the design of a distribution network for bottled drinks company is introduced. The distribution network proposed includes three stages: manufacturing centers, consolidation centers using cross-docking, and distribution centers. The problem is formulated using a mixed-integer programming model in the deterministic and single period contexts. Because the problem considers several elements in each stage, a direct solution is very complicated. For medium-to-large instances the problem falls into large scale. Based on that, a primal-dual decomposition known as cross decomposition is proposed in this paper. This approach allows exploring simultaneously the primal and dual subproblems of the original problem. A comparison of the direct solution with a mixed-integer lineal programming solver versus the cross decomposition is shown for several randomly generated instances. Results show the good performance of the method proposed.


DYNA ◽  
2015 ◽  
Vol 82 (191) ◽  
pp. 58-62 ◽  
Author(s):  
José Antonio Marmolejo-Saucedo ◽  
Román Rodríguez-Aguilar

<p class="ADYNAAbstrac"><span lang="EN-US">This paper addresses the short-term generation planning (STGP) through thermoelectric units. The mathematical model is presented as a Mixed Integer Non Linear Problem (MINLP). Several works on the state of art of the problem have revealed that the computational effort of this problem grows exponentially with the number of time periods and number of thermoelectric units. Therefore, we present two alternatives to solve a STGP based on Benders’ partitioning algorithm and Lagrangian relaxation in order to reduce the computational effort. The proposal is to apply primal and dual decomposition techniques, which exploit the structure of the problem to reduce solution time by decomposing the STGP into a master problem and a subproblem. For Benders’ algorithm, the master problem is a Mixed Integer Problem (MIP) and for the subproblem, it is a Non Linear Problem (NLP). For Lagrangian relaxation, the master problem and the subproblem are MINLP. The computational experiments show the performance of both decomposition techniques applied to the STGP. These techniques allow us to save computation time when compared to some high performance commercial solvers.</span></p>


2005 ◽  
Author(s):  
Michael Paley ◽  
Georgiy Levchuk ◽  
David Clark

Author(s):  
Nobuo KISHI ◽  
Nozumu KOGISO ◽  
Kazuko MORIZAWA ◽  
Takashi SHIMOMURA ◽  
Toshiaki TSUJII ◽  
...  

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