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In the present paper we describe new heuristic technique, which can be applied to the optimization of pseudo-Boolean functions including Black-Box functions. This technique is based on a simple procedure which consists in transition from…

Neural and Evolutionary Computing · Computer Science 2019-08-05 Alexander A. Semenov

The CDCL algorithm is the leading solution adopted by state-of-the-art solvers for SAT, SMT, ASP, and others. Experiments show that the performance of CDCL solvers can be significantly boosted by embedding domain-specific heuristics,…

Artificial Intelligence · Computer Science 2016-11-17 Carmine Dodaro , Philip Gasteiger , Nicola Leone , Benjamin Musitsch , Francesco Ricca , Konstantin Schekotihin

We consider the problem of minimizing a sum of non-convex functions over a compact domain, subject to linear inequality and equality constraints. Approximate solutions can be found by solving a convexified version of the problem, in which…

Optimization and Control · Mathematics 2016-01-12 Madeleine Udell , Stephen Boyd

This paper presents a new safety specification method that is robust against errors in the probability distribution of disturbances. Our proposed distributionally robust safe policy maximizes the probability of a system remaining in a…

Optimization and Control · Mathematics 2018-10-05 Insoon Yang

In this paper we consider the discounted 0-1 knapsack problem (DKP), which is an extension of the classical knapsack problem where a set of items is decomposed into groups of three items. At most one item can be chosen from each group and…

Optimization and Control · Mathematics 2022-01-05 C. Wilbaut , R. Todosijevic , S. Hanafi , A. Fréville

In pseudo-boolean solving the currently most successful unit propagation strategy is a hybrid mode combining the watched literal scheme with the counting method. This short paper introduces new heuristics for this hybrid decision, which are…

Artificial Intelligence · Computer Science 2025-12-22 Mia Müßig , Jan Johannsen

In this paper we present a fast scalable heuristic for bin packing that partitions the given problem into identical sub-problems of constant size and solves these constant size sub-problems by considering only a constant number of bin…

Data Structures and Algorithms · Computer Science 2019-04-30 Srikrishnan Divakaran

The Variable Sized Bin Packing Problem has a wide range of application areas including packing, scheduling, and manufacturing. Given a list of items and variable sized bin types, the objective is to minimize the total size of the used bins.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-02 Qadha'a AlEnezi , Hosam AboElFotoh , Bader AlBdaiwi , Mohammad Ali AlMulla

In the article, within the framework of the Boolean Satisfiability problem (SAT), the problem of estimating the hardness of specific Boolean formulas w.r.t. a specific complete SAT solving algorithm is considered. Based on the well-known…

Artificial Intelligence · Computer Science 2023-12-19 Daniil Chivilikhin , Artem Pavlenko , Alexander Semenov

Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR's) are proposed…

Optimization and Control · Mathematics 2020-03-20 V. Cerone , S. M. Fosson , D. Regruto

A novel multiscale consensus-based optimization (CBO) algorithm for solving bi- and tri-level optimization problems is introduced. Existing CBO techniques are generalized by the proposed method through the employment of multiple interacting…

Optimization and Control · Mathematics 2025-06-23 Michael Herty , Yuyang Huang , Dante Kalise , Hicham Kouhkouh

Boolean Satisfiability (SAT) is a well-known NP-complete problem. Despite this theoretical hardness, SAT solvers based on Conflict Driven Clause Learning (CDCL) can solve large SAT instances from many important domains. CDCL learns clauses…

Artificial Intelligence · Computer Science 2021-05-12 Md Solimul Chowdhury , Martin Müller , Jia You

Multi-distribution learning (MDL), which seeks to learn a shared model that minimizes the worst-case risk across $k$ distinct data distributions, has emerged as a unified framework in response to the evolving demand for robustness,…

Machine Learning · Computer Science 2025-08-12 Zihan Zhang , Wenhao Zhan , Yuxin Chen , Simon S. Du , Jason D. Lee

Heuristic algorithms have shown a good ability to solve a variety of optimization problems. Stockpile blending problem as an important component of the mine scheduling problem is an optimization problem with continuous search space…

Neural and Evolutionary Computing · Computer Science 2021-02-11 Yue Xie , Aneta Neumann , Frank Neumann

We propose a novel approach to solving input- and state-constrained parametric mixed-integer optimal control problems using Differentiable Predictive Control (DPC). Our approach follows the differentiable programming paradigm by learning an…

Systems and Control · Electrical Eng. & Systems 2025-06-25 Ján Boldocký , Shahriar Dadras Javan , Martin Gulan , Martin Mönnigmann , Ján Drgoňa

In large-scale games, approximating the opponent's strategy space with a small portfolio of representative strategies is a common and powerful technique. However, the construction of these portfolios often relies on domain-specific…

Computer Science and Game Theory · Computer Science 2025-11-25 Karolina Drabent , Ondřej Kubíček , Viliam Lisý

This work considers infinite-horizon optimal control of positive linear systems applied to the case of network routing problems. We demonstrate the equivalence between Stochastic Shortest Path (SSP) problems and optimal control of a certain…

Optimization and Control · Mathematics 2026-02-17 David Ohlin , Anders Rantzer , Emma Tegling

In this paper infinite horizon optimal control problems for nonlinear high-dimensional dynamical systems are studied. Nonlinear feedback laws can be computed via the value function characterized as the unique viscosity solution to the…

Optimization and Control · Mathematics 2016-02-22 Alessandro Alla , Maurizio Falcone , Stefan Volkwein

Spectral clustering and its extensions usually consist of two steps: (1) constructing a graph and computing the relaxed solution; (2) discretizing relaxed solutions. Although the former has been extensively investigated, the discretization…

Machine Learning · Computer Science 2023-10-20 Hongyuan Zhang , Xuelong Li

Checklists have been widely recognized as effective tools for completing complex tasks in a systematic manner. Although originally intended for use in procedural tasks, their interpretability and ease of use have led to their adoption for…

Machine Learning · Computer Science 2024-11-27 Yukti Makhija , Edward De Brouwer , Rahul G. Krishnan
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