Article Preview
TopIntroduction And Background
The last changes in the world had seen the advent of new information technologies and communication such as the internet and social networks like Facebook and Twitter. The information has become a pillar of our civilization, no one can escape it and we find it everywhere. Hence, the evolution of operating systems and the variation of the device capabilities have augmented the complexity of the process and the sources of computer problems.
The appearance of computer technology has permitted humans to resolve many problems. Unfortunately, in the last decade a new class of problem has seen the light named NP complete where researchers have attempted to solve this kind of problems as efficiently as possible such as: SAT and 3SAT problems in Braich, Chelyapov, Johnson, Rothemund, and Adleman (2002), backpack problem in Lindstrom-Hazel (2008), linear optimization into integers in Bertsimas and Tsitsiklis (1997), multiprocessor scheduling in Hou, Ansari, and Ren (1994), colouring graph in Molloy and Reed (2013).....Etc. For many years, research has been directed toward the proposition of exact algorithms but only for polynomial cases. Nevertheless, the research has turned toward the heuristic methods allowed to find solutions generally good like the separation and evaluation method that had helped to solve these problems optimally, but often for small instances.
The current scientific world was considerably built up with the inaugural appearance of novel concepts and paradigm. The advancement of research and the number of inspiration sources founded in nature represent a genuine opportunity for the future. Actually, for each encountered problem, we must observe the nature; it may already have the same problem, where it had found solutions, long years ago. The bio-mimicry consists to copy the living and doing research, otherwise, get advantage of solutions and innovations made by nature. This discipline is in strong growth, it is the heart of the innovation strategies of companies in many different sectors. Innovate by being frugal in energy and resources, is now viewed as the only solution to evolve the technologies, in many areas. There are three levels of bio-mimicry we can inspire from forms, manufacturing and processes of ecosystems, for example singing of the toad to improve Wi-Fi.
Around this topical science, several studies have been conducted over the behaviour of insects such as: social bees and their life that ensures the right functioning of the hive through the distribution of tasks between the worker bees (Karaboga & Basturk, 2007). The ants colony, this type of insect that lives in a company very organized based on the principle of discovering the shortest path by the mean of pheromone communication between them (Dorigo, Maniezzo, & Colorni, 1996) …etc.
The swarm insects’ lifestyles, have become a means for researchers to create new artificial models called social inspired techniques in order to generate a new efficient solutions to deal with the NP-complete problem previously seen; they have invaded a several fields as data-mining, meta-heuristics and information retrieval. In order to solve complex problems and dealing different challenges, in the computer community, the content of our work is to develop a new artificial algorithm, inspired by the lifestyle of cockroaches and their collective behaviour who like living in group by the combination of the intelligence of every individual cockroach to have an optimal decision. With a communication mode without a conductor, a functioning as a decentralized system and the intelligence also distributed with the purpose is to solve complex tasks from the sum of individual interactions and their continuous adaptation to the changing environment.
To see the performance and the uses of our proposed algorithm ASC to solve an NP complete problem, we have decided to apply this algorithm for the text clustering problem.