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For deterministic and probabilistic programs we investigate the problem of program synthesis and program optimisation (with respect to non-functional properties) in the general setting of global optimisation. This approach is based on the…

Programming Languages · Computer Science 2014-07-22 Herbert Wiklicky

We present a polynomial-time algorithm that obtains a set of Asymptotic Linear Programs (ALPs) from a given linear system S, such that one of these ALPs admits a feasible solution if and only if S admits a feasible solution. We also show…

Computational Complexity · Computer Science 2012-06-20 Deepak Ponvel Chermakani

A linear program with linear complementarity constraints (LPCC) requires the minimization of a linear objective over a set of linear constraints together with additional linear complementarity constraints. This class has emerged as a…

Optimization and Control · Mathematics 2018-02-09 Bin Yu , John E. Mitchell , Jong-Shi Pang

In order to handle the complexity and heterogeneity of mod- ern instruction set architectures, analysis platforms share a common design, the adoption of hardware-independent intermediate representa- tions. The usage of these platforms to…

Programming Languages · Computer Science 2018-07-30 Roberto Metere , Andreas Lindner , Roberto Guanciale

Education in the practical applications of logic and proving such as the formal specification and verification of computer programs is substantially hampered by the fact that most time and effort that is invested in proving is actually…

Logic in Computer Science · Computer Science 2018-03-06 Wolfgang Schreiner , Alexander Brunhuemer , Christoph Fürst

A numerical method is developed to solve linear semi-infinite programming problem (LSIP) in which the iterates produced by the algorithm are feasible for the original problem. This is achieved by constructing a sequence of standard linear…

Optimization and Control · Mathematics 2021-01-26 Shuxiong Wang

We introduce and study the infinite dimensional linear programming problem which along with its dual allows one to characterize the optimal value of the deterministic long-run average optimal control problem in the general case when the…

Optimization and Control · Mathematics 2018-05-08 Vivek S. Borkar , Vladimir Gaitsgory

Inductive logic programming (ILP) is a form of logical machine learning. The goal is to search a hypothesis space for a hypothesis that generalises training examples and background knowledge. We introduce an approach that 'shrinks' the…

Artificial Intelligence · Computer Science 2026-05-18 Andrew Cropper , Filipe Gouveia , David M. Cerna

Model execution allows us to prototype and analyse software engineering models by stepping through their possible behaviours, using techniques like animation and simulation. On the other hand, deductive verification allows us to construct…

Logic in Computer Science · Computer Science 2024-10-31 Simon Foster , Chung-Kil Hur , Jim Woodcock

It has been verified that the linear programming (LP) is able to formulate many real-life optimization problems, which can obtain the optimum by resorting to corresponding solvers such as OptVerse, Gurobi and CPLEX. In the past decades, a…

Optimization and Control · Mathematics 2022-01-19 Xijun Li , Qingyu Qu , Fangzhou Zhu , Jia Zeng , Mingxuan Yuan , Kun Mao , Jie Wang

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite…

Optimization and Control · Mathematics 2014-08-20 Vladimir Gaitsgory , Sergei Rossomakhine

Short integer linear programs are programs with a relatively small number of constraints. We show how recent improvements on the running-times of solvers for such programs can be used to obtain fast pseudo-polynomial time algorithms for…

Data Structures and Algorithms · Computer Science 2026-02-09 Danny Hermelin , Dvir Shabtay

Real-world optimization problems often do not just involve multiple objectives but also uncertain parameters. In this case, the goal is to find Pareto-optimal solutions that are robust, i.e., reasonably good under all possible realizations…

Optimization and Control · Mathematics 2023-11-06 Fabian Chlumsky-Harttmann , Marie Schmidt , Anita Schöbel

R\'esum\'e Apr\`es un bref aper\c{c}u permettant de situer notre travail, nous proposons une nouvelle voie pour aborder la programmation lin\'eaire en proposant un algorithme \'elabor\'e \`a partir d'une id\'ee simple qui permet d'obtenir…

Optimization and Control · Mathematics 2010-08-13 I. Faye , I. Lavallée , M. Ngom , D. Seck , A. Sy

In the hardware design process, hardware components are usually described in a hardware description language. Most of the hardware description languages, such as Verilog and VHDL, do not have mathematical foundation and hence are not fit…

Computation and Language · Computer Science 2022-02-10 Wilayat Khan , Zhe Hou , David Sanan , Jamel Nebhen , Yang Liu , Alwen Tiu

It has been recently established that a deterministic infinite horizon discounted optimal control problem in discrete time is closely related to a certain infinite dimensional linear programming problem and its dual. In the present paper,…

Optimization and Control · Mathematics 2018-02-19 Vladimir Gaitsgory , Alex Parkinson , Ilya Shvartsman

Algebraic characterization of logic programs has received increasing attention in recent years. Researchers attempt to exploit connections between linear algebraic computation and symbolic computation in order to perform logical inference…

Logic in Computer Science · Computer Science 2020-09-23 Tuan Nguyen Quoc , Katsumi Inoue , Chiaki Sakama

An infinite set is orbit-finite if, up to permutations of the underlying structure of atoms, it has only finitely many elements. We study a generalisation of linear programming where constraints are expressed by an orbit-finite system of…

Logic in Computer Science · Computer Science 2024-11-14 Arka Ghosh , Piotr Hofman , Sławomir Lasota

This paper proposes a new algorithm for linear system identification from noisy measurements. The proposed algorithm balances a data fidelity term with a norm induced by the set of single pole filters. We pose a convex optimization problem…

Optimization and Control · Mathematics 2012-04-04 Parikshit Shah , Badri Narayan Bhaskar , Gongguo Tang , Benjamin Recht

Linearisability has become the standard correctness criterion for concurrent data structures, ensuring that every history of invocations and responses of concurrent operations has a matching sequential history. Existing proofs of…

Logic in Computer Science · Computer Science 2013-07-29 Brijesh Dongol , John Derrick