Asynchronous P systems for SAT and Hamiltonian cycle problem

Ishii, Kota; Fujiwara, Akira; Tagawa, Hirofumi

doi:10.1109/nabic.2010.5716305

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…Since tissue-like P system is composed of basic cell units and cannot be separated from the properties of basic cells, a new membrane computing model is established by fusing the basic cell-like P system and the recognizable tissue-like P system [6] based on cell division. That is, the recognizable revolutionary tissue-like P system based on cell division can be used to solve the Satisfiability problem.…”

Section: Recognizable Evolutionary Tissue-like P Systemmentioning

confidence: 99%

Research of Improved Tissue-like P System for Solving Satisfiability Problem

2019

Electrical Engineering and Computer Science (EECS)

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Satisfiability problem is the first NP-complete problem that is not only the basic problem of logic but also the main content of computer science and artificial intelligence research nowadays. In this paper, the maximum parallelism of P system and the basic tissue-like P system are utilized to imitate life activities of charged organisms in nature; a recognizable evolutionary tissue-like P system based on cell division is proposed to solve the satisfiability problem. The system can obtain exponentially growing computing cells by cell division in a short time and each cell processes one truth value assignment situation; carries out parallel processing of the Boolean expression in polynomial time by using communication rules, splitting rule, evolutionary rule and output rules. To prove the correctness and efficiency of the algorithm, this paper completes the simulation of the algorithm by using pLingua Plugin that is dedicated to P system simulation, which proves that the algorithm is correct and feasible, and improves the calculation efficiency by changing the space for time.

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Section: Recognizable Evolutionary Tissue-like P Systemmentioning

confidence: 99%

Research of Improved Tissue-like P System for Solving Satisfiability Problem

2019

Electrical Engineering and Computer Science (EECS)

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“…A series of transfers of a system is called a computation, and the calculation result is defined as the objects that appear in a particular membrane (also known as the output membrane) at termination. As a typical type of NP problem, solving SAT problems with membrane computing has a long history [19][20][21][22][23]. Although membrane computing has strong computational power, it is predicted that there is still an upper limit, and therefore developing a new model of membrane computing for solving SAT problems that simplifies algorithms' structure is also important, which is the aim of this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Then for each membrane M i inside these two copies, judge the type of its inside clause r (20,21) , Figure 15 shows the membrane structure of this time.…”

mentioning

confidence: 99%

Enhanced Membrane Computing Algorithm for SAT Problems Based on the Splitting Rule

Hao

Liu

2019

Symmetry

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Boolean propositional satisfiability (SAT) problem is one of the most widely studied NP-complete problems and plays an outstanding role in many domains. Membrane computing is a branch of natural computing which has been proven to solve NP problems in polynomial time with a parallel compute mode. This paper proposes a new algorithm for SAT problem which combines the traditional membrane computing algorithm of SAT problem with a classic simplification rule, the splitting rule, which can divide a clause set into two axisymmetric subsets, deal with them respectively and simultaneously, and obtain the solution of the original clause set with the symmetry of their solutions. The new algorithm is shown to be able to reduce the space complexity by distributing clauses with the splitting rule repeatedly, and also reduce both time and space complexity by executing one-literal rule and pure-literal rule as many times as possible.

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“…For example, Ref. [11] proposes a P system to solve SAT problem based on the asynchronous parallelism. In Ref.…”

Section: Introductionmentioning

confidence: 99%