Bayesian Heuristic Approach (BHA) and Applications to Optimization of Large Scale Discrete and Continuous Models

1999 ◽  
pp. 249-260
Author(s):  
J. Mockus
Keyword(s):  
Large Scale ◽  
Heuristic Approach ◽  
Continuous Models

A spatial parallel heuristic approach for solving very large-scale vehicle routing problems

2017 ◽  
Vol 21 (6) ◽  
pp. 1130-1147 ◽  
Author(s):  
Wei Tu ◽  
Qingquan Li ◽  
Qiuping Li ◽  
Jiasong Zhu ◽  
Baoding Zhou ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Large Scale ◽  
Heuristic Approach ◽  
Vehicle Routing Problems ◽  
Routing Problems

scholarly journals The Design Principles of Discrete Turing Patterning Systems

2020 ◽  
Author(s):  
Tom Leyshon ◽  
Elisa Tonello ◽  
David Schnoerr ◽  
Heike Siebert ◽  
Michael P.H. Stumpf
Keyword(s):  
Cellular Automata ◽  
Large Scale ◽  
Turing Instability ◽  
Turing Patterns ◽  
Biochemical Processes ◽  
Modelling Framework ◽  
Underlying Principle ◽  
Continuous Models ◽  
Turing Instabilities ◽  
Definition Of

AbstractThe formation of spatial structures lies at the heart of developmental processes. However, many of the underlying gene regulatory and biochemical processes remain poorly understood. Turing patterns constitute a main candidate to explain such processes, but they appear sensitive to fluctuations and variations in kinetic parameters, raising the question of how they may be adopted and realised in naturally evolved systems. The vast majority of mathematical studies of Turing patterns have used continuous models specified in terms of partial differential equations. Here, we complement this work by studying Turing patterns using discrete cellular automata models. We perform a large-scale study on all possible two-node networks and find the same Turing pattern producing networks as in the continuous framework. In contrast to continuous models, however, we find the Turing topologies to be substantially more robust to changes in the parameters of the model. We also find that Turing instabilities are a much weaker predictor for emerging patterns in simulations in our discrete modelling framework. We propose a modification of the definition of a Turing instability for cellular automata models as a better predictor. The similarity of the results for the two modelling frameworks suggests a deeper underlying principle of Turing mechanisms in nature. Together with the larger robustness in the discrete case this suggests that Turing patterns may be more robust than previously thought.

scholarly journals Revisiting discrete versus continuous models of human behavior: The case of absolute pitch

2019 ◽  
Author(s):  
Stephen Charles Van Hedger ◽  
John Veillette ◽  
Shannon Heald ◽  
Howard Nusbaum
Keyword(s):  
Large Scale ◽  
Continuous Distribution ◽  
Absolute Pitch ◽  
Gaussian Mixture ◽  
Mixture Modeling ◽  
Inclusion Criteria ◽  
Cognitive Mechanisms ◽  
Developmental Factors ◽  
Gaussian Mixture Modeling ◽  
Continuous Models

Many human behaviors are discussed in terms of discrete categories. Quantizing behavior in this fashion may provide important traction for understanding the complexities of human experience, but it also may bias understanding of phenomena and associated mechanisms. One example of this is absolute pitch (AP), which is often treated as a discrete trait that is either present or absent (i.e., with easily identifiable near-perfect “genuine” AP possessors and at-chance non-AP possessors) despite emerging evidence that pitch-labeling ability is not all-or-nothing. We used a large-scale online assessment to test the discrete model of AP, specifically by measuring how intermediate performers related to the typically defined “non-AP” and “genuine AP” populations. Consistent with prior research, individuals who performed at-chance (non-AP) reported beginning musical instruction much later than the near-perfect AP participants, and the highest performers were more likely to speak a tonal language than were the lowest performers (though this effect was not as statistically robust as one would expect from prior research). Critically, however, these developmental factors did not differentiate the near-perfect AP performers from the intermediate AP performers. Gaussian mixture modeling supported the existence of two performance distributions – the first distribution encompassed both the intermediate and near-perfect AP possessors, whereas the second distribution encompassed only the at-chance participants. Overall, these results provide support for conceptualizing intermediate levels of pitch-labeling ability along the same continuum as genuine AP-level pitch labeling ability - in other words, a continuous distribution of AP skill among all above-chance performers rather than discrete categories of ability. Expanding the inclusion criteria for AP makes it possible to test hypotheses about the mechanisms that underlie this ability and relate this ability to more general cognitive mechanisms involved in other abilities.

A Heuristic Approach for Large Scale Job Shop Scheduling Problems

2008 ◽  
Vol 8 (6) ◽  
pp. 992-999
Author(s):  
M.H. Karimi Gav ◽  
M.H. Fazel Zara
Keyword(s):  
Large Scale ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Heuristic Approach ◽  
Scheduling Problems ◽  
Shop Scheduling

Providing consumers with a representative subset from online reviews

2017 ◽  
Vol 41 (6) ◽  
pp. 877-899 ◽  
Author(s):  
Jin Zhang ◽  
Ming Ren ◽  
Xian Xiao ◽  
Jilong Zhang
Keyword(s):  
Large Scale ◽  
User Study ◽  
Real Data ◽  
Online Reviews ◽  
Heuristic Approach ◽  
Online Information ◽  
Consumer Decision Making ◽  
High Coverage ◽  
Content Type ◽  
Representative Subset

Purpose The purpose of this paper is to find a representative subset from large-scale online reviews for consumers. The subset is significantly small in size, but covers the majority amount of information in the original reviews and contains little redundant information. Design/methodology/approach A heuristic approach named RewSel is proposed to successively select representatives until the number of representatives meets the requirement. To reveal the advantages of the approach, extensive data experiments and a user study are conducted on real data. Findings The proposed approach has the advantage over the benchmarks in terms of coverage and redundancy. People show preference to the representative subsets provided by RewSel. The proposed approach also has good scalability, and is more adaptive to big data applications. Research limitations/implications The paper contributes to the literature of review selection, by proposing a heuristic approach which achieves both high coverage and low redundancy. This study can be applied as the basis for conducting further analysis of large-scale online reviews. Practical implications The proposed approach offers a novel way to select a representative subset of online reviews to facilitate consumer decision making. It can also enhance the existing information retrieval system to provide representative information to users rather than a large amount of results. Originality/value The proposed approach finds the representative subset by adopting the concept of relative entropy and sentiment analysis methods. Compared with state-of-the-art approaches, it offers a more effective and efficient way for users to handle a large amount of online information.

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