An Aging Leader In The Elite Group-based Swarm Intelligent Algorithm For Intercell Scheduling Problems

The existence of intercell transfers has made the idea of creating independent cells impossible, intercell scheduling therefore comes into being. Owing to the limited capacity constraint, it is essential to coordinate between part scheduling and transportation among cells. In this paper, an intercell scheduling problem with a limited capacity constraint is considered. The complexity of the addressed problem is analyzed and it is worth an effort to study. Swarm intelligent algorithms are known to researchers for their robustness, flexibility and good labor division. As one of the swarm intelligent algorithms, artificial bee colony(ABC) algorithm plays an important role in part scheduling problems. An ABC with an aging leader in the elite group approach is proposed.Firstly, the intercell scheduling with limited transportation capacity is described and mathematically formulated given the constraints in practice.Secondly, an ABC with an aging leader in the elite group and transportation strategy(ALTSABC) approach is proposed. The colony of artificial bees is composed of employed bees, onlooker bees and scout bees. The basic ABC algorithm searches food sources iteratively through the following three phases. In the first phase, employed bee searches food sources in the neighborhood of the current position. In the second phase, a scout bee evaluates the information provided by employed bees. A food source is selected for further exploitation based on a binary tournament selection method. An aging mechanism namely aging leader in the elite group is used to guide the whole colony, so that the algorithm will not be trapped in local optima. In the third phase, a scout bee generates a new food source randomly once a food source is abandoned by an employed bee. When constructing solutions, a transportation strategy is designed. Each part is assigned a cost based on which a partial batch is formed on the vehicle without breaking the capacity constraint. Then, a heuristic is employed to determine the sequence of visiting different destination cells.Finally, several comparison experiments are conducted to evaluate the effectiveness of ALEGABC. The result shows that ALEGABC is better than the basic ABC algorithm in solution quality and speed of convergence. The comparison with other scheduling approaches again verifies the superiority of ALEGABC.