A State-of-the-Art Review of Biogeography-Based Optimization

Abstract

Biogeography-based optimization (BBO) is a population-based metaheuristic evolutionary algorithm proposed by Simon (IEEE Trans Evol Comput 12 (6):702-713, 2008 [1]). It is based on the theory of island biogeography which deals with the migration, speciation, and extinction of the species in a habitat. It has excellent exploitation ability but lacks in exploration. After the inception of BBO, a lot of modifications and hybridizations are introduced to enhance its performance. This paper focuses on various modifications and refinements in the migration and mutation operators of the original BBO and its hybridization with other populationbased meta-heuristic algorithms. In the end, some open problems related to BBO are highlighted encouraging future research in this novel area.Keywords Biogeography-based optimization (BBO) Á Meta-heuristic algorithms Á Migration BackgroundOptimization is the art of choosing the best among a vast set of alternatives subject to certain constraints. Many real-life problems can be modeled as nonlinear optimization problems. It is often necessary and desirable to determine the global optimal solution of such nonlinear optimization problems. To solve these problems, the conventional deterministic methods have inherent limitations for the purpose of implementation. Hence, the probabilistic techniques have become popular due to their ease of applicability although probabilistic techniques guarantee to reach the global optima only in the probabilistic sense. Nature-inspired optimization tech-

Financially embedded facility location decisions on designing a supply chain structure: A case study

“…Moreover, in order to provide a benchmark for the proposed NSGA‐II, there is a necessity to implement another optimization algorithm. Among the swarm‐based optimization methods, the MOBBO, as one of the state‐of‐the‐art algorithms, is employed . In the context of the proposed MOEAs, it should also be noted that the multiplicity of the solutions in a Pareto set may provide an element of doubt for decision makers to reach a final conclusion.…”

Efficient Mutation Strategies Embedded in Laplacian-Biogeography-Based Optimization Algorithm for Unconstrained Function Minimization

“…A real life problem using the proposed six different variants of LX-BBO is solved in this section. In Garg and Deep (2015) Stereo Camera Calibration Problem is solved. Stereo Camera Calibration Problem is an unconstrained continuous problem.…”

“…The results have been reported in the Table 5 and Table 6. Same parameters that have used in Garg and Deep (2015) are used to solve the camera calibration problem. The results of minimum camera errors of 50 independent runs for different number of control points are shown in Table 5 and Table 6.…”

“…Many attempts have been made in order to improve the exploring quality of BBO. An attempt is made in Garg and Deep, 2015 to collect different versions of improved BBO based on its migration and mutation operator. Gong et.al (2010) has tried to improve the exploration ability and population diversity of BBO by introducing different mutation operators.…”