Tracking Non-Stationary Optimal Solution by Particle Swarm Optimizer

Particle Swarm Social Adaptive Model for Multi-Agent Based Insurgency Warfare Simulation

“…As a result, the particle can be easily trapped in the region of the former optimal solution. Therefore, a memory update mechanism [3] is used to renew insurgent particles' memory when it is necessary. In this mechanism, a new notion, a evaporation constant T, is introduced.…”

RhoGTPase Involvement in Breast Cancer Migration and Invasion

“…When response is triggered by any of the various changes, each personal fitness value is decayed by multiplying it by a decay rate. Similar to PBDPSO, Tracking Dynamic PSO (TDPSO) [21] , uses an evaporation constant, to evaporate (decrease) the personal fitness value and global fitness value over time. Both of them renew their memory without any centralized control and to maintain simplicity of each particle.…”

“…The main advantage of such an approach is that it does not need a special operation to detect the environment changes [10,21]. This approach is appropriate for continuous small changes in the objective function.…”

“…A 3-dim parabolic function is adopted as a test function with linear, circular and random movement in [7] and a 10-dim one with linear movement is used in [6,22]. And a randomly moving optimal of the parabolic function also was used in [21]. Three types of dynamic optimum changes of DF1: small constant step changes, different large step changes, and chaotic step changes are used by Xiaodong [25] to compare several version PSO.…”

“…If all the dimensions are treated the same, we obtain n w i / 1 = . Then (20) can be written as (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21).…”