The Four-Block Model Matching Problem in $l^1 $ and Infinite-Dimensional Linear Programming

1993 ◽  
Vol 31 (3) ◽  
pp. 747-779 ◽  
Author(s):  
Olof J. Staffans
Keyword(s):  
Linear Programming ◽  
Model Matching ◽  
Block Model ◽  
Matching Problem ◽  
Infinite Dimensional

scholarly journals Shadow Prices in Infinite-Dimensional Linear Programming

1998 ◽  
Vol 23 (1) ◽  
pp. 239-256 ◽  
Author(s):  
H. Edwin Romeijn ◽  
Robert L. Smith
Keyword(s):  
Linear Programming ◽  
Shadow Prices ◽  
Infinite Dimensional

A Novel Approach for Business Process Model Matching Using Genetic Algorithms

2020 ◽  
Vol 12 (1) ◽  
pp. 1-19
Author(s):  
Mostefai Abdelkader ◽  
Ignacio García Rodríguez de Guzmán
Keyword(s):  
Genetic Algorithms ◽  
Business Process ◽  
Process Model ◽  
Optimization Problem ◽  
Process Models ◽  
Similarity Metrics ◽  
Model Matching ◽  
Matching Problem ◽  
Novel Approach ◽  
The One

This paper formulates the process model matching problem as an optimization problem and presents a heuristic approach based on genetic algorithms for computing a good enough alignment. An alignment is a set of not overlapping correspondences (i.e., pairs) between two process models(i.e., BP) and each correspondence is a pair of two sets of activities that represent the same behavior. The first set belongs to a source BP and the second set to a target BP. The proposed approach computes the solution by searching, over all possible alignments, the one that maximizes the intra-pairs cohesion while minimizing inter-pairs coupling. Cohesion of pairs and coupling between them is assessed using a proposed heuristic that combines syntactic and semantic similarity metrics. The proposed approach was evaluated on three well-known datasets. The results of the experiment showed that the approach has the potential to match business process models effectively.

scholarly journals The discrete-time tracking problem with H∞ model matching approach plus integral control

2019 ◽  
Vol 292 ◽  
pp. 01018
Author(s):  
Murat Akın ◽  
Tankut Acarman
Keyword(s):  
Discrete Time ◽  
Closed Loop ◽  
Controller Design ◽  
Model Matching ◽  
Matching Problem ◽  
Design Algorithm ◽  
Integral Control ◽  
Loop Transfer Function ◽  
Model Transfer ◽  
Static Output

In this study, the discrete-time H∞ model matching problem with integral control by using 2 DOF static output feedback is presented. First, the motivation and the problem is stated. After presenting the notation, the two lemmas toward the discrete-time H∞ model matching problem with integral control are proven. The controller synthesis theorem and the controller design algorithm is elaborated in order to minimize the H∞ norm of the closed-loop transfer function and to maximize the closed-loop performance by introducing the model transfer matrix. In following, the discrete-time H∞ MMP via LMI approach is derived as the main result. The controller construction procedure is implemented by using a well-known toolbox to improve the usability of the presented results. Finally, some conclusions are given.

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