scholarly journals Logic-Based Outer-Approximation Algorithm for Solving Discrete-Continuous Dynamic Optimization Problems

2014 ◽  
Vol 53 (13) ◽  
pp. 5067-5080 ◽  
Author(s):  
Ruben Ruiz-Femenia ◽  
Antonio Flores-Tlacuahuac ◽  
Ignacio E. Grossmann
Keyword(s):  
Approximation Algorithm ◽  
Dynamic Optimization ◽  
Optimization Problems ◽  
Outer Approximation ◽  
Dynamic Optimization Problems ◽  
Outer Approximation Algorithm ◽  
Continuous Dynamic

An adaptive bi-flight cuckoo search with variable nests for continuous dynamic optimization problems

2017 ◽  
Vol 48 (1) ◽  
pp. 97-117 ◽  
Author(s):  
Javidan Kazemi Kordestani ◽  
Hossein Abedi Firouzjaee ◽  
Mohammad Reza Meybodi
Keyword(s):  
Dynamic Optimization ◽  
Optimization Problems ◽  
Cuckoo Search ◽  
Dynamic Optimization Problems ◽  
Continuous Dynamic

An algorithm comparison for dynamic optimization problems

2012 ◽  
Vol 12 (10) ◽  
pp. 3176-3192 ◽  
Author(s):  
Ignacio G. del Amo ◽  
David A. Pelta ◽  
Juan R. González ◽  
Antonio D. Masegosa
Keyword(s):  
Dynamic Optimization ◽  
Optimization Problems ◽  
Dynamic Optimization Problems ◽  
Algorithm Comparison

scholarly journals Partially distributed outer approximation

2021 ◽  
Author(s):  
Alexander Murray ◽  
Timm Faulwasser ◽  
Veit Hagenmeyer ◽  
Mario E. Villanueva ◽  
Boris Houska
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Outer Approximation ◽  
Mixed Integer ◽  
Global Optimality ◽  
Integer Optimization ◽  
Global Minimizers ◽  
Outer Approximation Method ◽  
Coupling Constraints ◽  
Outer Approximation Algorithm

AbstractThis paper presents a novel partially distributed outer approximation algorithm, named PaDOA, for solving a class of structured mixed integer convex programming problems to global optimality. The proposed scheme uses an iterative outer approximation method for coupled mixed integer optimization problems with separable convex objective functions, affine coupling constraints, and compact domain. PaDOA proceeds by alternating between solving large-scale structured mixed-integer linear programming problems and partially decoupled mixed-integer nonlinear programming subproblems that comprise much fewer integer variables. We establish conditions under which PaDOA converges to global minimizers after a finite number of iterations and verify these properties with an application to thermostatically controlled loads and to mixed-integer regression.

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