Anaphora and Soft Constraints

1999 ◽  
pp. 1
Author(s):  
Luigi Burzio
Keyword(s):  
Soft Constraints

Exploiting Soft Constraints within Decomposition and Coordination Methods for Sub-hourly Unit Commitment

2020 ◽  
Author(s):  
Niranjan Raghunathan ◽  
Mikhail Bragin ◽  
Bing Yan ◽  
Peter Luh ◽  
Khosrow Moslehi ◽  
...  
Keyword(s):  
Unit Commitment ◽  
Daily Basis ◽  
Time Limit ◽  
Soft Constraints ◽  
Problem Complexity ◽  
Surrogate Optimization ◽  
Parallel Version ◽  
Improved Performance ◽  
Coordination Methods ◽  
Relaxed Problem

Unit commitment (UC) is an important problem solved on a daily basis within a strict time limit. While hourly UC problems are currently considered, they may not be flexible enough with the fast-changing demand and the increased penetration of intermittent renewables. Sub-hourly UC is therefore recommended. This, however, will significantly increase problem complexity even under the deterministic setting, and current methods may not be able to obtain good solutions within the time limit. In this paper, deterministic sub-hourly UC is considered, with the innovative exploitation of soft constraints – constraints that do not need to be strictly satisfied, but with predetermined penalty coefficients for their violations. The key idea is the “surrogate optimization” concept that ensures multiplier convergence within “surrogate” Lagrangian relaxation as long as the “surrogate optimality condition” is satisfied without the need to optimally solve the “relaxed problem.” Consequently, subproblems can still be formed and optimized when soft constraints are not relaxed, leading to a drastically reduced number of multipliers and improved performance. To further enhance the method, a parallel version is developed. Testing results on the Polish system demonstrate the effectiveness and robustness of both the sequential and parallel versions at finding high-quality solutions within the time limit.

scholarly journals A Fuzzy Optimization Model for High-Speed Railway Timetable Rescheduling

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Li Wang ◽  
Yong Qin ◽  
Jie Xu ◽  
Limin Jia
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
Fuzzy Optimization ◽  
Soft Constraints ◽  
Accurate Approximation ◽  
Total Delay ◽  
High Speed Rail ◽  
High Speed Railway ◽  
Tolerance Approach ◽  
Rail Line

A fuzzy optimization model based on improved symmetric tolerance approach is introduced, which allows for rescheduling high-speed railway timetable under unexpected interferences. The model nests different parameters of the soft constraints with uncertainty margin to describe their importance to the optimization purpose and treats the objective in the same manner. Thus a new optimal instrument is expected to achieve a new timetable subject to little slack of constraints. The section between Nanjing and Shanghai, which is the busiest, of Beijing-Shanghai high-speed rail line in China is used as the simulated measurement. The fuzzy optimization model provides an accurate approximation on train running time and headway time, and hence the results suggest that the number of seriously impacted trains and total delay time can be reduced significantly subject to little cost and risk.

Constraint-following servo control for an underactuated mobile robot under hard constraints

2021 ◽  
pp. 095965182110248
Author(s):  
Duo Fu ◽  
Jin Huang ◽  
Wen-Bin Shangguan ◽  
Hui Yin
Keyword(s):  
Mobile Robot ◽  
Control Problem ◽  
Servo Control ◽  
Robot Motion ◽  
Soft Constraints ◽  
Rigorous Proof ◽  
Control Approach ◽  
Hard Constraints

This article formulates the control problem of underactuated mobile robot as servo constraint-following, and develops a novel constraint-following servo control approach for underactuated mobile robot under both servo soft and hard constraints. Servo soft constraints are expressed as equalities, which may be holonomic or non-holonomic. Servo hard constraints are expressed as inequalities. It is required that the underactuated mobile robot motion eventually converges to servo soft constraints, and satisfies servo hard constraints at all times. Diffeomorphism is employed to incorporate hard constraints into soft constraints, yielding new soft constraints to relax hard constraints. By this, we design a constraint-following servo control based on the new servo soft constraints, which drives the system to strictly follow the original servo soft and hard constraints. The effectiveness of the proposed approach is proved by rigorous proof and simulations.

Preference reasoning with soft constraints in constraint-based recommender systems

Constraints ◽  
2010 ◽  
Vol 15 (4) ◽  
pp. 574-595 ◽  
Author(s):  
Markus Zanker ◽  
Markus Jessenitschnig ◽  
Wolfgang Schmid
Keyword(s):  
Recommender Systems ◽  
Soft Constraints ◽  
Preference Reasoning

Structure determination of the 1/1 α/β mixed lactose by X-ray powder diffraction

2005 ◽  
Vol 61 (4) ◽  
pp. 455-463 ◽  
Author(s):  
Jacques Lefebvre ◽  
Jean-François Willart ◽  
Vincent Caron ◽  
Ronan Lefort ◽  
Frédéric Affouard ◽  
...  
Keyword(s):  
Powder Diffraction ◽  
Size Effects ◽  
Room Temperature ◽  
Real Space ◽  
Hydroxyl Groups ◽  
Soft Constraints ◽  
Rietveld Refinements ◽  
X Ray ◽  
Mixed Compound

The mixed form of α/β lactose was obtained by heating amorphous α-lactose at 443 K. NMR spectroscopy determined the stoichiometry of this mixed compound to be 1/1. The X-ray powder diffraction pattern was recorded at room temperature with a sensitive curved detector (CPS 120). The structure was solved by real-space methods (simulated annealing) followed by Rietveld refinements with soft constraints on bond lengths and bond angles. The H atoms of the hydroxyl groups were localized by minimization of the crystalline energy. The cell of 1/1 α/β lactose is triclinic with the space group P1 and contains two molecules (one molecule of each anomer). The crystalline cohesion is achieved by networks of O—H...O hydrogen bonds. The width of the Bragg peaks is interpreted through a microstructural approach in terms of isotropic strain effects and anisotropic size effects.

3D genome structure reconstruction from chromosomal contact data

2017 ◽  
Author(s):  
◽  
Tuan Anh Trieu
Keyword(s):  
High Resolution ◽  
Genome Structure ◽  
Cell Types ◽  
3D Models ◽  
Graphic User Interface ◽  
Soft Constraints ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Manual Adjustment ◽  
The Relationship

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Different cell types of an organism have the same DNA sequence, but they can function differently because their difference in 3D organization allows them to express different genes and has different cellular functions. Understanding the 3D organization of the genome is the key to understand functions of the cell. Chromosome conformation capture techniques like Hi-C and TCC that can capture interactions between proximal chromosome fragments have allowed the study of 3D genome organization in high resolution and high through-put. My work focuses on developing computational methods to reconstruct 3D genome structures from Hi-C data. I presented three methods to reconstruct 3D genome and chromosome structures. The first method can build 3D genome models from soft constraints of contacts and non-contacts. This method utilizes the concept of contact and non-contact to reconstruct 3D models without translating interaction frequencies into physical distances. The translation is commonly used by other methods even though it makes a strong assumption about the relationship between interaction frequencies and physical distances. In synthetic dataset, when the relationship was known, my method performed comparably with other methods assuming the relationship. This shows the potential of my method for real Hi-C datasets where the relationship is unknown. The limitation of the method is that it has parameters requiring manual adjustment. I developed the second method to reconstruct 3D genome models. This method utilizes a commonly used function to translate interaction frequencies to physical distances to build 3D models. I proposed a novel way to derive soft constraints to handle inconsistency in the data and to make the method robust. Building 3D models at high resolution is a more challenging problem as the number of constraints is small and the feasible space is larger. I introduced a third method to build 3D chromosome models at high resolution. The method reconstructs models at low resolution and then uses them to guide the reconstruction of models at high resolution. The last part of my work is the development of a comprehensive tool with intuitive graphic user interface to analyze Hi-C data, reconstruct and analyze 3D models.

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