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The Artificial Bee Colony (ABC) algorithm as a non-standard computational method

Swarm intelligence is defined in the academic literature as the ability to design algorithms inspired by the collective behaviour of decentralized and self-organized social insect colonies. A well-known example of swarm intelligence is a honey bee swarm which has enthused researchers to develop algorithms based on the various activities taking place within a bee colony. An example of one such algorithm is the Artificial Bee Colony (ABC) algorithm proposed by Karaboga in 2005 which simulates the foraging behavior of bees for solving optimization problems and is the one of the most widely studied swarm based algorithms so far.

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Risks in large scale IT projects

As always happens, large IT projects are exposed to adverse influences, the so called project risks, which may result in delaying the timely completion of the project, increasing the cost or reducing the final quality of the product. Project risks affect all aspects of a software project: the organization, the personnel, the technology etc. and can prevent the intended benefit of the project being realised. Generally speaking, various types of risks leading to project failure exist.

First, the so-called schedule risks reflect the fact that schedules often slip and the product is not delivered on time. Among the reasons for these risks are wrong time estimation, resources not tracked properly, failure to identify complex functionalities and time required to develop them, unexpected project scope expansions and lack of agreement between customer and developer.

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