A Novel Discrete Bacterial Foraging Algorithm and Its Application

Abstract

In order to solve discrete optimization problems, this paper proposed a discrete bacterial foraging algorithm (DBFA) based on the idea of bacterial foraging optimization (BFO). The proposed DBFA applies binary encoding, and thus has the advantages of solving both discrete and continuous optimization problems. Also, according to sharing experiences of bacterium, we use the rotation step to update velocities of bacteria and obtain its corresponding positions. Then we evaluate the efficiency of the proposed algorithm through three classical benchmark functions and spectrum allocation problem of cognitive radio. Simulation results show that the proposed algorithm is superior to some previous intelligence algorithms in both convergence rate and convergence accuracy. A key advance will be met by a significant reduction in computational time-costs whilst further improving the global search capabilities of the algorithm. Cognitive radio (CR) provides a feasible solution for dynamic spectrum access. It solves the contradiction between the scarcity of spectrum resources and increasing radio access demands through letting the secondary users use the available spectrum while avoiding interference with the primary users and their neighbors. Based on centralized or distributed architecture, cooperative or non-cooperative spectrum allocation behavior, overlay or underlay spectrum access technique, lots of models have been proposed for dynamic spectrum access, including game theory (5), pricing and auction mechanisms (6)(7), local bargaining (8) and graph coloring (9). Assuming that the environmental conditions are static during the time it takes to perform spectrum assignment, an allocation model is proposed in (10), and color sensitive graph coloring (CSGC) is used to solve the allocation problem.