Parallel solutions to intractable problems in industrial processes

• Grant number: 15/18164-5
• Support Opportunities: Regular Research Grants
• Start date: December 01, 2015
• End date: November 30, 2017
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Theory of Computation
• Principal Investigator: Carlos Alberto Alonso Sanches
• Grantee: Carlos Alberto Alonso Sanches
• Host Institution: Divisão de Ciência da Computação (IEC). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil

Abstract

The purpose of this aid is the acquisition of equipment for implementing and testing of parallel algorithms to intractable problems, which do not have polynomial-time resolutions on serial computers. The current focus is to find efficient algorithms to Knapsack Problem and Minimization of Open Stacks Problem, which are common in industrial processes, and their multicore and GPU implementations, devices with a high degree of parallel processing, affordable cost and low energy consumption. We also intend to acquire computers to prepare articles, attend conferences and conduct distance meetings. Guidelines are provided for students at various levels (Scientific Initiation, Completion of Course Work, Master and PhD), with the corresponding publications in indexed vehicles (conferences and journals). (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SANCHES, C. A. A.; SOMA, N. Y.. A general resolution of intractable problems in polynomial time through DNA Computing. BIOSYSTEMS, v. 150, p. 119-131, DEC 2016. (15/18164-5)

CURTIS, V. V.; SANCHES, C. A. A.. An improved balanced algorithm for the subset-sum problem. European Journal of Operational Research, v. 275, n. 2, p. 460-466, JUN 1 2019. (15/18164-5)

CURTIS, V. V.; SANCHES, C. A. A.. A low-space algorithm for the subset-sum problem on GPU. Computers & Operations Research, v. 83, p. 120-124, JUL 2017. (15/18164-5)