Invasive weed optimization algorithm

The invasive weed optimization (IWO) algorithm is a numerical optimization algorithm inspired by weed colonization; it is a form of evolutionary algorithm. According to the common definition, a weed is any plant growing where it is not wanted. Any tree, vine, shrub, or herb may qualify as a weed, depending on the situation; generally, however, the term is reserved for those plants whose vigorous, invasive habits of growth pose a serious threat to desirable, cultivated plants. Weeds have a very robust and adaptive nature, undesirable traits in agriculture.
Why weeds are important?
A plant is called weed if, in any specified geographical area, its populations grow entirely or predominantly in situations markedly disturbed by man (without, of course, being deliberately cultivated plants). The most interesting feature of weeds that is now become a common belief in agronomy it that “The Weeds Always Win”. The harder people try, the better they get:
* After many thousands of years of tillage and hand-weeding we still have weeds.
* After 50 years of herbicides we still have weeds in the same fields.
* In every field, in every year, we always miss some weeds.
* New weed species appear frequently, spreading across the country.
* No weed species have disappeared from production fields.
* Humans have recently created an entirely new category of very nasty weeds: herbicide resistant weeds.
These properties indicates that the weeds are of the most robust and troublous plants in agriculture. It is also a confirmation of the fact that weeds adapt with environment and change their behavior and gets better (fitter). Weed biology and ecology is the story of their success.
The algorithm
To simulate colonizing behavior of weeds some basic properties of the process is considered:
# A finite number of seeds are being dispread over the search area (initializing a population),
# Every seeds grows to a flowering plant and produces seeds depending on their fitness (reproduction),
# The produced seeds are being randomly dispread over the search area and grow to new plants (spatial dispersal),
# This process continues until maximum number of plants is reached; now only the plants with lower fitness can survive and produce seeds, others are being eliminated (competitive exclusion). The course continues until maximum iterations is reached and hopefully the plant with best fitness it the closest to the optimal solution.

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