Experimental and Simulation Design of an Engineering Scheduling Problem Based on Molecular Computing Approach

2007 ◽  
pp. 178-182
Author(s):  
Mohd Saufee Muhammad ◽  
Osamu Ono
Keyword(s):  
Molecular Computing ◽  
Scheduling Problem ◽  
Simulation Design ◽  
Computing Approach

A reservoir computing approach for molecular computing

2018 ◽  
Author(s):  
Wataru Yahiro ◽  
Nathanael Aubert-Kato ◽  
Masami Hagiya
Keyword(s):  
Molecular Computing ◽  
Reservoir Computing ◽  
Computing Approach

A Molecular Solution to the Three-Partition Problem

2012 ◽  
Vol 5 (4) ◽  
pp. 14-29
Author(s):  
Maryam S. Nuser
Keyword(s):  
Molecular Computing ◽  
Partition Problem ◽  
Biomolecular Computing ◽  
Hard Problems ◽  
Np Complete ◽  
Computing Approach

Given a set of numbers, the three-partition problem is to divide them into disjoint triplets that all have the same sum. The problem is NP-complete. This paper presents an algorithm to solve this problem using the biomolecular computing approach. The algorithm uses a distinctive encoding technique that depends on the numbers values which omits the need to an adder to find the sum. The algorithm is explained and an analysis of its complexity in terms of time, the number of strands, number of tubes, and the longest library strand used is presented. A simulation of the algorithm is implemented and tested. This algorithm further proves the ability of molecular computing in solving hard problems.

Solving Elevator Scheduling Problem Using DNA Computing Approach

2007 ◽  
pp. 359-370 ◽  
Author(s):  
Mohd Saufee Muhammad ◽  
Satomi Ueda ◽  
Osamu Ono ◽  
Junzo Watada ◽  
Marzuki Khalid
Keyword(s):  
Dna Computing ◽  
Scheduling Problem ◽  
Computing Approach

scholarly journals A molecular computing approach to solving optimization problems via programmable microdroplet arrays

Matter ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 1107-1124
Author(s):  
Si Yue Guo ◽  
Pascal Friederich ◽  
Yudong Cao ◽  
Tony C. Wu ◽  
Christopher J. Forman ◽  
...  
Keyword(s):  
Optimization Problems ◽  
Molecular Computing ◽  
Computing Approach

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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