A polynomial-time algorithm for optimization of quadratic pseudo-boolean functions

Mulero Martínez,

Juan Ignacio

Published: May 13, 2020

In this paper, an exact algorithm in polynomial time is developed to solve unrestricted binary quadratic programs. The computational complexity $O\left( n^{\frac{15}{2}}\right) $, although very conservative, it sufficient prove that minimization problem the class $P$. implementation aspects are also described detail with a special emphasis on transformation of program into linear can be solved time. was implemented MATLAB and checked by generating five million matrices arbitrary dimensions up 30 random entries range $\left[ -50,50\right] $. All experiments carried out have revealed method works correctly.

Language: Английский

Pseudo-Boolean optimization DOI
Endre Boros,

Peter L. Hammer

Discrete Applied Mathematics, Journal Year: 2002, Volume and Issue: 123(1-3), P. 155 - 225

Published: Nov. 1, 2002

Language: Английский

Citations

799

Genetic algorithms with local improvement for composite laminate design DOI
Nozomu KOGISO,

L. T. Watson,

Z. Gürdal

et al.

Structural Optimization, Journal Year: 1994, Volume and Issue: 7(4), P. 207 - 218

Published: June 1, 1994

Language: Английский

Citations

172

On the complexity of local search DOI Open Access
Christos H. Papadimitriou, Alejandro A. Schäffer, Mihalis Yannakakis

et al.

Published: Jan. 1, 1990

Article Free Access Share on On the complexity of local search Authors: C. H. Papadimitriou Department Computer Science and Engineering, University California at San Diego DiegoView Profile , A. Schäffer Science, Rice UniversityView M. Yannakakis AT&T Bell Laboratories. Laboratories.View Authors Info & Claims STOC '90: Proceedings twenty-second annual ACM symposium Theory ComputingApril 1990Pages 438–445https://doi.org/10.1145/100216.100274Published:01 April 1990Publication History 68citation1,337DownloadsMetricsTotal Citations68Total Downloads1,337Last 12 Months108Last 6 weeks16 Get Citation AlertsNew Alert added!This alert has been successfully added will be sent to:You notified whenever a record that you have chosen cited.To manage your preferences, click button below.Manage my Alert!Please log in to account Save BinderSave BinderCreate New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Language: Английский

Citations

112

Computational Complexity as an Ultimate Constraint on Evolution DOI Open Access
Artem Kaznatcheev

Genetics, Journal Year: 2019, Volume and Issue: 212(1), P. 245 - 265

Published: March 4, 2019

Experiments show that evolutionary fitness landscapes can have a rich combinatorial structure due to epistasis. For some landscapes, this produce computational constraint prevents evolution from finding local optima-thus overturning the traditional assumption peaks always be reached quickly if no other forces challenge natural selection. Here, I introduce distinction between easy of theory where found in moderate number steps, and hard optima requires an infeasible amount time. Hard examples exist even among with reciprocal sign epistasis; on these semismooth strong selection weak mutation dynamics cannot find unique peak polynomial More generally, rugged include epistasis, dynamics-even ones do not follow adaptive paths-can optimum quickly. Moreover, advantage nearby mutants drop off exponentially fast but has power-law long-term experiments associated unbounded growth fitness. Thus, complexity enables open-ended finite landscapes. Knowing allows us use tools theoretical computer science optimization characterize we expect see nature. present candidates for at scales single genes, microbes, complex organisms costly learning (Baldwin effect) or maintained cooperation (Hankshaw effect). Just how ubiquitous (and corresponding ultimate evolution) are nature becomes open empirical question.

Language: Английский

Citations

67

DESIGN OF COMPOSITE LAMINATES BY A GENETIC ALGORITHM WITH MEMORY DOI
Nozomu KOGISO, Layne T. Watson,

Z. Gürdal

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 1994, Volume and Issue: 1(1), P. 95 - 117

Published: Sept. 1, 1994

Abstract This paper describes the use of a genetic algorithm with memory for design minimum thickness composite laminates subject to strength, buckling and ply contiguity constraints. A binary tree is used efficiently store retrieve information about past designs. construct set linear approximations load in neighbourhood each member population The are then seek nearby improved designs procedure called local improvement. demonstrates that this substantially reduces number analyses required search. also algorithms helps find several alternative similar performance, thus giving designer choice alternatives.

Language: Английский

Citations

90

Local optimization on graphs DOI
Donna Llewellyn, Craig A. Tovey, Michael A. Trick

et al.

Discrete Applied Mathematics, Journal Year: 1989, Volume and Issue: 23(2), P. 157 - 178

Published: May 1, 1989

Language: Английский

Citations

74

The analysis of local search problems and their heuristics DOI
Mihalis Yannakakis

Lecture notes in computer science, Journal Year: 1990, Volume and Issue: unknown, P. 298 - 311

Published: Jan. 1, 1990

Language: Английский

Citations

65

Recognition problems for special classes of polynomials in 0–1 variables DOI
Yves Crama

Mathematical Programming, Journal Year: 1989, Volume and Issue: 44(1-3), P. 139 - 155

Published: May 1, 1989

Language: Английский

Citations

51

On the Complexity of the Policy Improvement Algorithm for Markov Decision Processes DOI

Mary Melekopoglou,

Anne Condon

INFORMS Journal on Computing, Journal Year: 1994, Volume and Issue: 6(2), P. 188 - 192

Published: May 1, 1994

We consider the complexity of policy improvement algorithm for Markov decision processes. show that four variants require exponential time in worst case. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Computing from 1989 to 1995 under 0899-1499.

Language: Английский

Citations

50

Combinatorial structure and randomized subexponential algorithms for infinite games DOI Creative Commons
Henrik Björklund,

Sergei Vorobyov

Theoretical Computer Science, Journal Year: 2005, Volume and Issue: 349(3), P. 347 - 360

Published: Oct. 3, 2005

Language: Английский

Citations

41