The pit-trapping foraging strategy of the ant lion, Myrmeleon immaculatus DeGeer (Neuroptera: Myrmeleontidae)

1984 ◽  
Vol 14 (2) ◽  
pp. 151-160 ◽  
Author(s):  
Bernd Heinrich ◽  
Margaret J. E. Heinrich
2020 ◽  
Vol 14 (4) ◽  
pp. 727-735
Author(s):  
Huanlong Zhang ◽  
Zeng Gao ◽  
Jie Zhang ◽  
Xiankai Lu ◽  
Jian Chen ◽  
...  
Keyword(s):  

2020 ◽  
pp. 1-13
Author(s):  
Gokul Chandrasekaran ◽  
P.R. Karthikeyan ◽  
Neelam Sanjeev Kumar ◽  
Vanchinathan Kumarasamy

Test scheduling of System-on-Chip (SoC) is a major problem solved by various optimization techniques to minimize the cost and testing time. In this paper, we propose the application of Dragonfly and Ant Lion Optimization algorithms to minimize the test cost and test time of SoC. The swarm behavior of dragonfly and hunting behavior of Ant Lion optimization methods are used to optimize the scheduling time in the benchmark circuits. The proposed algorithms are tested on p22810 and d695 ITC’02 SoC benchmark circuits. The results of the proposed algorithms are compared with other algorithms like Ant Colony Optimization, Modified Ant Colony Optimization, Artificial Bee Colony, Modified Artificial Bee Colony, Firefly, Modified Firefly, and BAT algorithms to highlight the benefits of test time minimization. It is observed that the test time obtained for Dragonfly and Ant Lion optimization algorithms is 0.013188 Sec for D695, 0.013515 Sec for P22810, and 0.013432 Sec for D695, 0.013711 Sec for P22810 respectively with TAM Width of 64, which is less as compared to the other well-known optimization algorithms.


Author(s):  
Haneul Jang ◽  
Rahayu Oktaviani ◽  
Sanha Kim ◽  
Ani Mardiastuti ◽  
Jae C. Choe

Author(s):  
Poppy M. Jeffries ◽  
Samantha C. Patrick ◽  
Jonathan R. Potts

AbstractMany animal populations include a diversity of personalities, and these personalities are often linked to foraging strategy. However, it is not always clear why populations should evolve to have this diversity. Indeed, optimal foraging theory typically seeks out a single optimal strategy for individuals in a population. So why do we, in fact, see a variety of strategies existing in a single population? Here, we aim to provide insight into this conundrum by modelling the particular case of foraging seabirds, that forage on patchy prey. These seabirds have only partial knowledge of their environment: they do not know exactly where the next patch will emerge, but they may have some understanding of which locations are more likely to lead to patch emergence than others. Many existing optimal foraging studies assume either complete knowledge (e.g. Marginal Value Theorem) or no knowledge (e.g. Lévy Flight Hypothesis), but here we construct a new modelling approach which incorporates partial knowledge. In our model, different foraging strategies are favoured by different birds along the bold-shy personality continuum, so we can assess the optimality of a personality type. We show that it is optimal to be shy (resp. bold) when living in a population of bold (resp. shy) birds. This observation gives a plausible mechanism behind the emergence of diverse personalities. We also show that environmental degradation is likely to favour shyer birds and cause a decrease in diversity of personality over time.


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