How to use dynamic soaring by the Albatrosses in optimization?

What is dynamic soaring?

The dynamic soaring mainly consists of four phases.

Upward Bind

Upward Climb

Downward Bind

Downward Dive

This four-phase consists of a cycle which is referred to as Rayleigh’s Cycles as he was the first to identify this phenomenon by Albatrosses during their long-time flights.

For more details refer to Richardson(2011 & 2014), Uesaka et.al.(2023), etc.

Criteria of Dynamic Soaring

In general, albatross soaring can be accomplished under the following conditions: (1) no wind, no waves, no soaring;(2) Wave-slope soaring can be accomplished in swell without wind; (3) Wind–shear soaring can be accomplished in wind without waves.

What is Wind Shear Soaring?

The average wind speed typically rises with height, starting at almost zero at the ocean's surface. Within about two meters of the water's surface, a thin boundary layer has the greatest vertical wind velocity gradient (largest wind shear) (Fig. 2). In this narrow wind–shear boundary layer close to the surface, the majority of the wind speed increase in an average wind profile occurs.

What is Wave Slope Soaring?

There is an accepted notion that wind moving up a wave's windward face is what primarily causes updrafts over waves (see Pennycuick, 1982, Wilson, 1975). Updrafts, however, have much more intricate structures and causes, such as air displaced upward by the wave surface's orbital velocity and vertical velocities resulting from wind–wave interactions. Both of these can happen at the same time, and they have complex interactions with one another.

What happened during the dynamic soaring of the bird?

When there is no wind and waves on the ocean surface the bird can not soar. But the birds can soar when there is wind speed near the ocean surface is much less compared to that at the higher layers that are located above the heights of the ocean waves. These two zones of different air speeds are separated by the wind shear layer. Now at the time of the upward climb bird tries to extract energy from the interaction of wind with the wave in the lower layers i.e. below the wave height (eg. updrafts or leeways or eddy currents of the waves). This energy is mainly gained at the time of upward bend and used at the time of climb. At this moment both the wind and the bird face the wave head-on.

After it crosses the wind shear if it again tries to come back to the lower layer it extracts the energy from the downward wind at the time of the downward bend and uses it at the time of the downward dive. This time both wind and bird are facing the wave surface at their backside.

Introduction to Glowworm Optimization Algorithm

Overview of the Glow Worm Algorithm Explanation of the original Glow Worm Algorithm The Hybrid Glow Worm Algorithm is an important algorithm to study and understand because of its ability to effectively solve complex optimization problems. By combining the strengths of different algorithms, it offers a flexible and adaptable solution approach that can be applied to various domains. Understanding this algorithm can help researchers and practitioners in developing efficient and effective optimization strategies for their specific problem instances. The original Glow Worm Algorithm is a swarm intelligence-based optimization algorithm inspired by the behavior of glow worms in nature. It involves a population of virtual glow worms that interact with each other and their environment to find optimal solutions. The algorithm uses a combination of local and global search strategies, allowing the glow worms to explore and exploit the search space effectively. Additionally, the algorithm incor

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