The Bees Algorithm and Its Applications

The Bees Algorithm (BA) is a swarm-based optimization algorithm inspired by the food foraging behavior of honeybees. The aim of this chapter is to describe a swarm-based optimization algorithm called the Bees Algorithm and its applications to real world problems. After an explanation of the natural foraging behavior of honeybees, the basic Bees Algorithm and its enhanced version based on Adaptive Neighborhood Search and Site Abandonment (ANSSA) strategy are described and two applications are discussed in detail. The first application deals with the optimization of several benchmark functions and the results obtained by the ANSSA-based BA is compared with the basic BA and other optimization algorithms. The second application deals with the multi-objective optimization problem in finding the best supply chain configuration

A Hybrid Approach using the Bees Algorithm and Fuzzy-AHP for Supplier Selection

In this chapter, a new hybrid approach combining the Fuzzy Analytic Hierarchy Process (AHP) and the Bees Algorithm is proposed in order to solve the supplier selection problem. The Fuzzy Analytic Hierarchy Process is used to determine the importance weight of each criterion and sub-criterion considered for the supplier selection, which are quality, cost, service level, supplier profile and risk. These weights are utilized in a mathematical model to determine the optimum order level of each row material from each supplier. The model considers capacity, demand, on-time delivery, quality and bill of materials. To determine the optimum order levels, the Bees Algorithm is applied to optimize this NP-hard type model under the constraints. The results showed that the Bees Algorithm performed better than Genetic Algorithm during the optimization stage