A Crossover Bacterial Foraging Optimization Algorithm

This paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using crossover mechanism is to search nearby locations by offspring (50 percent of bacteria), because they are randomly produced at different locations. In the traditional bacterial foraging optimization algorithm, search starts from the same locations (50 percent of bacteria are replicated) which is not desirable. Seven different benchmark functions are considered for performance evaluation. Also, comparison with the results of previous methods is presented to reveal the effectiveness of the proposed algorithm

An Enhanced Approach for Image Edge Detection Using Histogram Equalization (BBHE) and Bacterial Foraging Optimization (BFO)

The Edge detection is a customarily task. Edge detection is the main task to perform as it gives clear information about the images. It is a tremendous device in photograph processing gadgets and computer imaginative and prescient. Previous research has been done on moving window approach and genetic algorithms. In this research paper new technique, Bacterial Foraging Optimization (BFO) is applied which is galvanized through the social foraging conduct of Escherichia coli (E.coli). The Bacterial Foraging Optimization (BFO) has been practice by analysts for clarifying real world optimization problems arising in different areas of engineering and application domains, due to its efficiency. The Brightness preserving bi-histogram equalization (BHEE) is another technique that is used for edge enhancement. The BFO is applied on the low level characteristics on the images to find the pixels of natural images and the values of F-measures, recall(r) and precision (p) are calculated and compared with the previous technique. The enhancement technique i.e. BBHE is carried out to improve the information about the pictures

Bacterial-foraging optimization algorithm for non-hazardous plant layouts

PresentationThe following article approaches a safe plant layout design problem based on a bacterial-foraging optimization algorithm. Our approach finds the position in the two dimensional plane for each main process unit and evaluates the possibility of secondary contention for pertinent units, in order to minimize capital costs associated to equipment loss, piping, secondary contention, and usage of area. Fire and Explosion hazard is considered as the relevant safety aspect for distribution, and it is assessed through Dow’s Fire and Explosion Index. The proposed solution approach provides an alternative to hard-optimization methods, by allowing greater flexibility in accounting for both safety and economic aspects, while providing high quality solutions in a limited computation time. The aim of our proposed solution approach is to provide support to expert decision-making during the early plant layout design steps. A case study based on an acrylic-acid production plant, which has been used by several other papers that appeared in the literature, serves the purposes of showing the appropriateness and effectiveness of the method

An Enhanced Approach for Image Edge Detection Using Histogram Equalization (BBHE) and Bacterial Foraging Optimization (BFO)

The Edge detection is a customarily task. Edge detection is the main task to perform as it gives clear information about the images. It is a tremendous device in photograph processing gadgets and computer imaginative and prescient. Previous research has been done on moving window approach and genetic algorithms. In this research paper new technique, Bacterial Foraging Optimization (BFO) is applied which is galvanized through the social foraging conduct of Escherichia coli (E.coli). The Bacterial Foraging Optimization (BFO) has been practice by analysts for clarifying real world optimization problems arising in different areas of engineering and application domains, due to its efficiency. The Brightness preserving bi-histogram equalization (BHEE) is another technique that is used for edge enhancement. The BFO is applied on the low level characteristics on the images to find the pixels of natural images and the values of F-measures, recall(r) and precision (p) are calculated and compared with the previous technique. The enhancement technique i.e. BBHE is carried out to improve the information about the pictures