scholarly journals Solving Multidimensional 0-1 Knapsack Problem with Time-Free Tissue P Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Xiangrong Liu ◽  
Ziming Li ◽  
Juan Suo ◽  
Ying Ju ◽  
Juan Liu ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Knapsack Problem ◽  
Execution Time ◽  
Efficient Solution ◽  
P Systems ◽  
Distributed Model ◽  
P System ◽  
Biological Processes ◽  
Execution Times ◽  
Tissue P System

Tissue P system is a class of parallel and distributed model; a feature of traditional tissue P system is that the execution time of certain biological processes is very sensitive to environmental factors that might be hard to control. In this work, we construct a family of tissue P systems that works independently from the values associated with the execution times of the rules. Furthermore, we present a time-free efficient solution to multidimensional 0-1 knapsack problem by timed recognizer tissue P systems.

Time-Free Solution for QSAT by Using Timed Tissue P Systems

2014 ◽  
Vol 568-570 ◽  
pp. 812-816 ◽  
Author(s):  
Yun Yun Niu ◽  
Zhi Gao Wang
Keyword(s):  
Computational Efficiency ◽  
Execution Time ◽  
Realistic Model ◽  
Point Of View ◽  
P Systems ◽  
P System ◽  
Free Solution ◽  
Complete Problem ◽  
Computational Processes ◽  
Tissue P System

A timed tissue P system is constructed by adding a time mapping to the rules of tissue P system to specify the execution time for each rule. It is a more realistic model from a biological point of view. In this study, we investigate the computational efficiency of timed tissue P systems. A uniform and time-free solution to QSAT problem, a famous PSPACE-complete problem, is proposed, where the execution time of the computational processes involved can vary arbitrarily and the output produced is always the same.

Time-Free Spiking Neural P Systems

2011 ◽  
Vol 23 (5) ◽  
pp. 1320-1342 ◽  
Author(s):  
Linqiang Pan ◽  
Xiangxiang Zeng ◽  
Xingyi Zhang
Keyword(s):  
Environmental Factors ◽  
P Systems ◽  
P System ◽  
Spiking Neural P Systems ◽  
Computation Result ◽  
Semilinear Sets ◽  
Execution Times ◽  
Definition Of ◽  
Robust Systems

Different biological processes take different times to be completed, which can also be influenced by many environmental factors. In this work, a realistic definition of nonsynchronized spiking neural P systems (SN P systems, for short) is considered: during the work of an SN P system, the execution times of spiking rules cannot be known exactly (i.e., they are arbitrary). In order to establish robust systems against the environmental factors, a special class of SN P systems, called time-free SN P systems, is introduced, which always produce the same computation result independent of the execution times of the rules. The universality of time-free SN P systems is investigated. It is proved that these P systems with extended rules (several spikes can be produced by a rule) are equivalent to register machines. However, if the number of spikes present in the system is bounded, then the power of time-free SN P systems falls, and in this case, a characterization of semilinear sets of natural numbers is obtained.

scholarly journals Time-Free Solution to SAT Problem by Tissue P Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Yueguo Luo ◽  
Zhongyang Xiong ◽  
Guanghua Zhang
Keyword(s):  
Intercellular Communication ◽  
Execution Time ◽  
Efficient Solution ◽  
Point Of View ◽  
P Systems ◽  
Free Solution ◽  
Complete Problem ◽  
Np Complete ◽  
First Time ◽  
Computing Models

Tissue P systems are a class of computing models inspired by intercellular communication, where the rules are used in the nondeterministic maximally parallel manner. As we know, the execution time of each rule is the same in the system. However, the execution time of biochemical reactions is hard to control from a biochemical point of view. In this work, we construct a uniform and efficient solution to the SAT problem with tissue P systems in a time-free way for the first time. With the P systems constructed from the sizes of instances, the execution time of the rules has no influence on the computation results. As a result, we prove that such system is shown to be highly effective for NP-complete problem even in a time-free manner with communication rules of length at most 3.

scholarly journals An Adaptive Optimization Spiking Neural P System for Binary Problems

2020 ◽  
Vol 31 (01) ◽  
pp. 2050054 ◽  
Author(s):  
Ming Zhu ◽  
Qiang Yang ◽  
Jianping Dong ◽  
Gexiang Zhang ◽  
Xiantai Gou ◽  
...  
Keyword(s):  
Knapsack Problem ◽  
Membrane Computing ◽  
Combinatorial Problems ◽  
P Systems ◽  
P System ◽  
Adaptive Optimization ◽  
Spiking Neural P System ◽  
Multiple Faults ◽  
Computing Model ◽  
Bus System

Optimization Spiking Neural P System (OSNPS) is the first membrane computing model to directly derive an approximate solution of combinatorial problems with a specific reference to the 0/1 knapsack problem. OSNPS is composed of a family of parallel Spiking Neural P Systems (SNPS) that generate candidate solutions of the binary combinatorial problem and a Guider algorithm that adjusts the spiking probabilities of the neurons of the P systems. Although OSNPS is a pioneering structure in membrane computing optimization, its performance is competitive with that of modern and sophisticated metaheuristics for the knapsack problem only in low dimensional cases. In order to overcome the limitations of OSNPS, this paper proposes a novel Dynamic Guider algorithm which employs an adaptive learning and a diversity-based adaptation to control its moving operators. The resulting novel membrane computing model for optimization is here named Adaptive Optimization Spiking Neural P System (AOSNPS). Numerical result shows that the proposed approach is effective to solve the 0/1 knapsack problems and outperforms multiple various algorithms proposed in the literature to solve the same class of problems even for a large number of items (high dimensionality). Furthermore, case studies show that a AOSNPS is effective in fault sections estimation of power systems in different types of fault cases: including a single fault, multiple faults and multiple faults with incomplete and uncertain information in the IEEE 39 bus system and IEEE 118 bus system.

scholarly journals Solving the 0-1 Knapsack Problem by Using Tissue P System With Cell Division

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 66055-66067 ◽  
Author(s):  
Lian Ye ◽  
Jinhang Zheng ◽  
Ping Guo ◽  
Mario J. Perez-Jimenez
Keyword(s):  
Cell Division ◽  
Knapsack Problem ◽  
P System ◽  
Tissue P System

Preemptive Scheduling for Two-Processor Systems

1988 ◽  
Vol 11 (1) ◽  
pp. 1-19
Author(s):  
Andrzej Rowicki
Keyword(s):  
Execution Time ◽  
Preemptive Scheduling ◽  
Total Execution Time ◽  
Schedule Length ◽  
Execution Times ◽  
Dependent Tasks

The purpose of the paper is to consider an algorithm for preemptive scheduling for two-processor systems with identical processors. Computations submitted to the systems are composed of dependent tasks with arbitrary execution times and contain no loops and have only one output. We assume that preemptions times are completely unconstrained, and preemptions consume no time. Moreover, the algorithm determines the total execution time of the computation. It has been proved that this algorithm is optimal, that is, the total execution time of the computation (schedule length) is minimized.

scholarly journals Novel Numerical Spiking Neural P Systems with a Variable Consumption Strategy

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 549
Author(s):  
Xiu Yin ◽  
Xiyu Liu ◽  
Minghe Sun ◽  
Qianqian Ren
Keyword(s):  
Production Functions ◽  
P Systems ◽  
P System ◽  
Computing Device ◽  
Spiking Neural P Systems ◽  
Distributed Parallel Computing ◽  
Production Values ◽  
Novel Variant ◽  
Turing Universality ◽  
Variable Consumption

A novel variant of NSN P systems, called numerical spiking neural P systems with a variable consumption strategy (NSNVC P systems), is proposed. Like the spiking rules consuming spikes in spiking neural P systems, NSNVC P systems introduce a variable consumption strategy by modifying the form of the production functions used in NSN P systems. Similar to the delay feature of the spiking rules, NSNVC P systems introduce a postponement feature into the production functions. The execution of the production functions in NSNVC P systems is controlled by two, i.e., polarization and threshold, conditions. Multiple synaptic channels are used to transmit the charges and the production values in NSNVC P systems. The proposed NSNVC P systems are a type of distributed parallel computing models with a directed graphical structure. The Turing universality of the proposed NSNVC P systems is proved as number generating/accepting devices. Detailed descriptions are provided for NSNVC P systems as number generating/accepting devices. In addition, a universal NSNVC P system with 66 neurons is constructed as a function computing device.

Properties of n-alcohol + n-alkane mixtures

1977 ◽  
Vol 30 (1) ◽  
pp. 43 ◽  
Author(s):  
F Smith
Keyword(s):  
P Systems ◽  
Effect Of Temperature ◽  
P System ◽  
Range Data ◽  
Free Energies ◽  
Dipole Term ◽  
Partial Molar Enthalpies ◽  
Refined Estimate ◽  
Two Parameters ◽  
Latent Heats

The total polar contributions (AP) to three properties [infrared absorbance, mixing enthalpies (HM) and excess free energies (GE)] of alcohol + alkane (alp) systems are separated into a direct hydrogenbond contribution ( AB) from the formation of isolated imers and a dipole-dipole contribution (AD) resulting from dipolar correlation between these transient imers. Dilute concentration range data giving the AB contributions to these properties were found dependent only on OH group concentration (c) and are used to show the serious inadequacies of previous theories. A new proposed association model having only two parameters, that are fixed for all systems, does give good results for the AB contributions and further is quite compatible with the effect of temperature change and with the n.m.r. chemical shift (ε) and apparent mean square dipole moment (p2) data that are also studied. Thus association theory has been made quantitative for the AB contributions to three properties of a/p systems and the approach given for deriving models appears capable of wider application. The model was used to extrapolate the AB contributions into the concentrated alcohol range to thus give the AD contributions by difference. The latter are then shown to be the origin of the distinctive behaviour shown by lower alcohols in their pure and binary mixture properties either with alkanes or with other alcohols where for the latter the principle of congruence is shown to be completely misleading. Two contributions (Ag and AD) explain the different c dependence shown by the i.r., HM and the δ data for a/p systems and, qualitatively, the HM data for alcohol+alcohol systems while the existence of a significant dipole term is strongly supported by the remarkable similarities found between the p2(c) data and the derived dipole-dipole contribution to the entropy of a/p systems. A method is given for predicting latent heats and partial molar enthalpies of higher alcohols from the HM data for one a/p system and a refined estimate is made of the enthalpy of formation of a hydrogen bond. Polar structure and non-linear dielectric effects are also discussed.

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