Discussions of worker ants' rule-based CHC dealing with changing environments

Authors:
Akimoto Kamiya;Kazuya Abiko;Shigenobu Kobayashi
Affiliations:
Department of Information Engineering, Kushiro National College of Technology, 2-32-1 Otanoshike-nishi, Kushiro 084-0916, Japan;Nikon Corporation, 471 Nagaodai-machi, Sakae-ku, Yokohama 244-8533, Japan;Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta Midori-ku, Yokohama 226-8502, Japan
Venue:
Applied Soft Computing
Year:
2010

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Abstract

Contrary to popular belief, biologists discovered that worker ants are really not all hardworking. It has been found that in three separate 30-strong colonies of black Japanese ants (Myrmecina nipponica), about 20% of worker ants are diligent, 60% are ordinary, and 20% are lazy. That is called 20:60:20 rule. Though they are lazy, biologists suggested that lazy worker ants could be contributing something to the colony that is yet to be determined. In our last research, we used CHC (cross generational elitist selection, heterogeneous recombination, and cataclysmic mutation) with the worker ants' rule (WACHC) aiming at solving optimization problems in changing environments. CHC is a nontraditional genetic algorithm (GA) which combines a conservative selection strategy that always preserves the best individuals found so far with a radical (highly disruptive) recombination operator. In our last research, we verified that WACHC performs better than CHC in only one case of fully changing environment. In this paper, we further discuss our proposed WACHC dealing with changing environment problems with varying degree of difficulty, compare our proposal with hypermutation GA which is also proposed for dealing with changing environment problems, and discuss the difference between our proposal and ant colony optimization algorithms.