Dynamic abstractions and reformulations in constraint satisfaction problems

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Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances. A primal- ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state ...

Adiabatic quantum-flux-parametron (AQFP) circuits are a family of superconducting electronic (SCE) circuits that have recently gained growing interest due to their low-energy consumption, and may serve as alternative technology to overcome the down-scaling ...

Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

We consider various versions of the obstacle and thin-obstacle problems, we interpret them as variational inequalities, with non-smooth constraint, and prove that they satisfy a new constrained Lojasiewicz inequality. The difficulty lies in the fact that, ...

Localization of a set of nodes is an important and a thoroughly researched problem in robotics and sensor networks. This paper is concerned with the theory of localization from inner-angle measurements. We focus on the challenging case where no anchor loca ...

Neural networks are increasingly used in complex (data-driven) simulations as surrogates or for accelerating the computation of classical surrogates. In many applications physical constraints, such as mass or energy conservation, must be satisfied to obtai ...

Modeling and Simulation (M&S) is one of the most multifaceted topics present today in both industry and academia. However, we are involved in a new M&S paradigm. Systems are becoming more complex and new simulation needs arise and have to be studied. As a ...

This paper addresses the steady-state optimization of continuous processes in the presence of uncertainty in the form of unknown or time-varying model parameters, structural plant-model mismatch, and disturbances. To address these issues, we assume that ce ...

Optimization of industrial processes aims at minimizing operating cost or maximizing economic profit while respecting plant constraints. In process industry, real-time optimization (RTO) is often considered to ensure optimal plant operation and constraint ...

SAT based exact synthesis is a powerful technique, with applications in logic optimization, technology mapping, and synthesis for emerging technologies. However, its runtime behavior can be unpredictable and slow. In this paper, we propose to add a new typ ...

Multi-objective optimization tools are becoming increasingly popu-lar in mechanical engineering and allow decision-makers to better understand the inevitable trade-offs. Mechanical design problems can however combine properties that make the use of optimiz ...

Due to recent advances, constraint solvers have become efficient tools for synthesizing optimum Boolean circuits. We take advantage of this by showing how SAT based exact synthesis may be used as a method for finding minimum length Boolean chains. As oppos ...

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not ...

This paper describes synthesis of controllers involving Quadratic Programming (QP) optimization problems for control of nonlinear systems. The QP structure allows an implementation of the controller as a piecewise affine function, pre-computed offline, whi ...

Holant is a framework of counting characterized by local constraints. It is closely related to other well-studied frameworks such as the counting constraint satisfaction problem (#CSP) and graph homomorphism. An effective dichotomy for such frameworks can ...

The steady advances of computational methods make model-based optimization an increasingly attractive method for process improvement. Unfortunately, the available models are often inaccurate. The traditional remedy is to update the model parameters, but th ...

Dynamic abstractions and reformulations in constraint satisfaction problems

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