In this chapter an overview on the Bee Colony Optimization (BCO) method is presented. In the first introductory section the development of the BCO algorithm is given, with an overview on history of mathematical model based on discovered behavior patterns in bees in early 1940s. The aim here is to remind of first steps made in solving of optimization problems by BCO and what kind of changes were performed to obtain the current versions of the BCO method. In the second section two variants of the BCO algorithm are described in great details.
At the end a short overview on the various applications of the BCO method is listed. Bee colony optimization is a population-based meta-heuristic method that was first proposed by Lu\v{c}i\'c and Teodorovi\'c …show more content…
Seeley was inspired with progress made in models of bumble bees. He recognized that even though much has been done to understand inner working of honey bees colonies, a lot was still remained to be discovered \cite{seely1995}. The initial study he conducted together with his colleague Kirk Visscher, reviled a great deal of new insights, like those that bees make individual assessments of a food source's absolute quality, or that the honey bees can cover more then $100$ square kilometers around the hive during foraging. In joint work with Camazine and Sneyd, Seeley showed that waggle dance of the worker bees is changing in relation to the absolute quality of a food source. When the quality of the food is high, the foraging bees dance longer and more vigorously \cite{seeley1991,seeley2000}. It can be noted that to conclude a mathematical model of this mechanism is a quite ambitious task. Main problem is that much of the inner workings of honey bees may not be correctly described \cite{seely1995}. However, the pursuit towards simplification of the living processes can also lead to interesting discoveries and tools that can be used for solving hard real world …show more content…
They postulated that the collective memory is shared via the dance language and presented a model that describes the colony's decision-making process using system of non-linear differential equations that has most affect on the total foraging success. This model, however, disregarded some aspects of honey bees foraging process, like individual behavior. In many papers this problem was referred, with a still open question about how important is the ``dance language'' for communicating memory. In the paper \cite{granovskiy2012} this issue was addressed in order to understand the importance of the direct sharing of information through the waggle dance. The experimental results have show that the drop in total foraging success, when the use of dance language was removed, was not as drastic as proposed in models of
Seeley. Another also interesting question concerns the imprecision of information being shared, which can influence on fertility of new food sources of high quality.
The complexity of the insects behavior still today cannot be replicated with mathematical models. Nonetheless, the imitation of only a small part of
At the end a short overview on the various applications of the BCO method is listed. Bee colony optimization is a population-based meta-heuristic method that was first proposed by Lu\v{c}i\'c and Teodorovi\'c …show more content…
Seeley was inspired with progress made in models of bumble bees. He recognized that even though much has been done to understand inner working of honey bees colonies, a lot was still remained to be discovered \cite{seely1995}. The initial study he conducted together with his colleague Kirk Visscher, reviled a great deal of new insights, like those that bees make individual assessments of a food source's absolute quality, or that the honey bees can cover more then $100$ square kilometers around the hive during foraging. In joint work with Camazine and Sneyd, Seeley showed that waggle dance of the worker bees is changing in relation to the absolute quality of a food source. When the quality of the food is high, the foraging bees dance longer and more vigorously \cite{seeley1991,seeley2000}. It can be noted that to conclude a mathematical model of this mechanism is a quite ambitious task. Main problem is that much of the inner workings of honey bees may not be correctly described \cite{seely1995}. However, the pursuit towards simplification of the living processes can also lead to interesting discoveries and tools that can be used for solving hard real world …show more content…
They postulated that the collective memory is shared via the dance language and presented a model that describes the colony's decision-making process using system of non-linear differential equations that has most affect on the total foraging success. This model, however, disregarded some aspects of honey bees foraging process, like individual behavior. In many papers this problem was referred, with a still open question about how important is the ``dance language'' for communicating memory. In the paper \cite{granovskiy2012} this issue was addressed in order to understand the importance of the direct sharing of information through the waggle dance. The experimental results have show that the drop in total foraging success, when the use of dance language was removed, was not as drastic as proposed in models of
Seeley. Another also interesting question concerns the imprecision of information being shared, which can influence on fertility of new food sources of high quality.
The complexity of the insects behavior still today cannot be replicated with mathematical models. Nonetheless, the imitation of only a small part of