根系协调优化(RSCO)在经济负荷调度中的应用

Vivekananda Haldar, N. Chakraborty
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引用次数: 0

摘要

植物的根和芽(绿色区域)相互协调,生长得更快。它通过汁液的上升、蒸腾的拉动、茎和根之间的压力以及溶质的传导,以一种优化的方式来实现这一目标。随着树叶数量的增加,有更多的阳光。另一方面,根通过破坏和压碎地壳下的物质来分叉和延伸,以增加宽度和长度,以寻找足够的水源。根茎协调优化(RSCO)是一种基于生理过程的自然启发的元启发式方法,已应用于经济负荷调度问题。研究表明,RSCO算法在经济负荷调度问题上的性能优于Real编码遗传算法、加速粒子群算法和粒子群算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Root Shoot Coordination Optimization (RSCO) for economic load dispatch
The root and shoot (greenish area) in plant coordinate with each other to grow faster. It does that in an optimized way through ascent of sap, transpiration pull, pressure built up between shoot and root and conduction of solute. With that the number of leaf increases to have more sunlight. On the other hand root ramificates and extends by breaking and crushing the material underneath the earth crust to grow in width and length for finding adequate source of water. This physiological process based nature inspired meta-heuristic technique named Root Shoot Coordination Optimization (RSCO) has been applied on economic load dispatch problem. It has been observed that RSCO performs well in comparison to Real Coded Genetic Algorithm, Accelerated Particle Swarm Optimization and Particle Swarm Optimization for economic load dispatch problem.
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