LIP: a data path scheduler using linear integer programming

2003 ◽  
Author(s):  
Jiahn-Hurng Lee ◽  
Yu-Chin Hsu ◽  
Youn-Long Lin
Keyword(s):  
Integer Programming ◽  
Data Path ◽  
Linear Integer Programming

Linear Integer Programming

2021 ◽  
Author(s):  
Elias Munapo ◽  
Santosh Kumar
Keyword(s):  
Integer Programming ◽  
Linear Integer Programming

scholarly journals An exact algebraic ϵ-constraint method for bi-objective linear integer programming based on test sets

2020 ◽  
Vol 282 (2) ◽  
pp. 453-463
Author(s):  
María Isabel Hartillo-Hermoso ◽  
Haydee Jiménez-Tafur ◽  
José María Ucha-Enríquez
Keyword(s):  
Integer Programming ◽  
Linear Integer Programming ◽  
Test Sets ◽  
Constraint Method

scholarly journals Smart Health Model With A Linear Integer Programming Approach

2019 ◽  
Vol 1361 ◽  
pp. 012069 ◽  
Author(s):  
A M H Pardede ◽  
H Mawengkang ◽  
M Zarlis ◽  
T Tulus ◽  
L A N Kadim ◽  
...  
Keyword(s):  
Integer Programming ◽  
Programming Approach ◽  
Linear Integer Programming ◽  
Smart Health ◽  
Health Model

scholarly journals An Integrated Approach to Data Path Synthesis for Behavioral-level Power Optimization

VLSI Design ◽  
2000 ◽  
Vol 11 (4) ◽  
pp. 381-396
Author(s):  
Chaeryung Park ◽  
Taewhan Kim ◽  
C. L. Liu
Keyword(s):  
Integer Programming ◽  
Power Consumption ◽  
Efficient Algorithm ◽  
Integrated Approach ◽  
Data Path ◽  
Programming Formulation ◽  
Prior Work ◽  
Design Problems ◽  
Path Synthesis ◽  
Important Design

This paper presents an integrated approach to data path synthesis which solves three important design problems: scheduling, allocation, and hardware partitioning with power minimization as a key design objective. Based on the rules of thumbs introduced in prior work on synthesis for low power we derive an integer programming formulation for solving the problems. We then, based on the formulation, develop an efficient algorithm which performs scheduling, allocation and hardware partitioning simultaneously so that the effects of them on power consumption are exploited more fully and effectively. Our experimentation results show that the algorithm is quite effective, producing designs with significant savings in power consumption.

A novel optimal configuration of sensor and actuator using a non-linear integer programming genetic algorithm for active vibration control

2017 ◽  
Vol 28 (15) ◽  
pp. 2074-2081 ◽  
Author(s):  
Chunyou Zhang ◽  
Lihua Wang ◽  
Xiaoqiang Wu ◽  
Weijin Gao
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Flexible Structures ◽  
Linear Quadratic ◽  
Linear Integer Programming ◽  
Optimal Criterion ◽  
Non Linear ◽  
Active Vibration

Due to widespread applications of a large number of flexible structures, to obtain the best dynamic control performance of a system, optimal locations of the actuators and sensors are necessary to be determined. This article proposes a novel optimal criterion for the actuators or sensors ensuring good controllability or observability of a structure, and also considering the remaining modes to control the spillover effect. Based on the proposed optimization criteria, a non-linear integer programming genetic algorithm is employed to achieve the optimal configurations. Active vibration control is investigated for a cantilever plate with the actuators in optimal positions to suppress the specified modes utilizing linear quadratic regulator controller. Several simulation results validate the efficiency and feasibility of the proposed optimal criteria.

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