ABSTRACT
An optimization technique called ‘Artificial Bee Colony’ was developed, inspired by the intelligent foraging behaviour (searching for food resources) of honeybees. There are three parameters of primary importance in the foraging behaviour of honeybees: food source (nectar), employed foragers and unemployed foragers. This behaviour leads to two modes, i.e., consumption and abandonment of nectar source. The colony of bees generally contains two groups of bees: employed bees and onlooker bees. The employed bees have all the information about the source (nectar position) and quality of food (nectar amount). In the hive, all the employed bees start waggle dance. This dance is the indication of all the characteristics of their foods, i.e., the amount as well as the quality of foods. The same hive also shelters unemployed bees called onlooker bees. They watch the waggle dance and get the information about all the food sources and get attracted to the best food source. This educates onlooker bees and converts them to employed bees, and they start consuming the nectar from the best food source. When this food source becomes abandoned, the employed bee becomes a scout bee and starts looking for a new food source. As a scout finds a new food source, it becomes an employed bee and the cycle goes on until the best food source (optimum solution) is obtained. In a similar fashion, an artificial bee colony (ABC) algorithm has been employed in this chapter to investigate the effect of machining parameters on the Surface Roughness in wire electrical discharge machining (WEDM), another non-conventional machining method, and an optimal combination of input parameters for minimum Surface Roughness is obtained. The experimental studies were conducted based on central composite design method, and subsequently, regression model using response surface methodology (RSM) was developed. Surface plots were generated to study the effect, and the surface topology caused by WEDM is analysed by Scanning Electron Microscopy images.
