Executive Summary HSABC Algorithm

Random walks are important for mimicking erratic movements which applying to a randomly chosen current location moves to a new selected destination. In nature, bees randomly move when foraging for foods from a selected current food source to positions corresponding to nectar amounts. Colonies of honeybees can extend over long distances and in multiple directions simultaneously in order to exploit many food sources. During the harvest season, flowers bloom in an area around the hive with certain qualities of nectars. Bees continue to randomly explore for additional food sources within the area. Harvest Season Artificial Bee Colony, HSABC, Algorithm covers the multiple food sources, multiple locations of food sources, and a harvest operator. Graphically, the mechanism of HSABC when searching for the food is illustrated in Figure 1 and Figure 2 shows two-dimensional flower placements for the random-walk analysis. In principle, the sequencing computation of the HSABC algorithm is distributed into several phases to select the optimal solution. By considering the stages of food selection, bee’s phases are transferred into pseudo-codes as following orders: Initial Phase: create an initial population set of candidate solutions for multiple food sources and evaluate the population for each food. Employed Bees Phase: produce a new position of a food source, produce a new position of a food source during harvest season for the position, evaluate each food source, apply the greedy process for multiple food sources, and calculate the probability values of multiple food sources. Onlooker Bees Phase: produce a new solution for a new position, produce a new solution of harvest season for the position, evaluate solutions and apply the greedy process to foods from multiple positions. Scout Bees Phase: determine an abandoned solution for the scout bee, replace with a new randomly produced solution, and memorize the optimal solution achieved so far.