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Biogeography-based optimization (BBO) is a population-based evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the science and study of the geographical distribution of biological organisms. In BBO, problem solutions are analogous to islands, and the sharing of features between solutions is analogous to the migration of(More)
—Biogeography-based optimization (BBO) is an evolutionary algorithm that is based on the science of biogeography. Biogeography is the study of the geographical distribution of organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration between islands. This paper develops a(More)
—Biogeography-based optimization (BBO) is a recently developed heuristic algorithm which has shown impressive performance on many well known benchmarks. In order to improve BBO, this paper incorporates distinctive features from other successful heuristic algorithms into BBO. In this paper, features from evolutionary strategy (ES) are used for BBO(More)
We show that biogeography-based optimization (BBO) is a generalization of a genetic algorithm with global uniform recombination (GA/GUR). Based on the common features of BBO and GA/GUR, we use a previously-derived BBO Markov model to obtain a GA/GUR Markov model. One BBO characteristic which makes it distinctive from GA/GUR is its migration mechanism, which(More)
Despite much demonstrated success, existing methods are less effective for applications that entail online processing. Examples abound, including video surveillance, action recognition and human-computer interaction, to name a few. Recently, some online video segmentation methods are proposed, e.g., [4] and [6]. The global object appearance modeling without(More)
Biogeography-based optimization (BBO) is a population-based evolutionary algorithm (EA) that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration. BBO is(More)
In recent years, most effective multi-object tracking (MOT) methods are based on the tracking-by-detection framework. Existing performance evaluations of MOT methods usually separate the target association step from the object detection step by using the same object detection results for comparisons. In this work, we perform a comprehensive quantitative(More)