umeshan pillay - Academia.edu (original) (raw)

Papers by umeshan pillay

IEEE Access

The use of metaheuristic, nature inspired algorithms for solving complex optimization problems wi... more The use of metaheuristic, nature inspired algorithms for solving complex optimization problems with non-linearity and multimodality, has become a popular tool in the field of science and engineering. Presently, there has been much development of such tools, with academics creating new natureinspired algorithms that could potentially be more efficient and effective. One such algorithm is the Flower Pollination Algorithm (FPA) developed by Xin-She Yang in 2012. This metaheuristic algorithm is modelled after the evolutionary process of flowering plants and has been useful in many fields of science and engineering, particularly electrical Power Systems, which forms the basis for modern day life and is responsible for meeting worldwide needs for reliable generation, transmission, and distribution of power. With the rapid expansion of industries and population growth, power utilities are faced with the arduous task of satisfying these needs. In addition, utilities are met with common problems, such as economic load dispatch, power quality improvement etc. To assist in solving these problems, FPA has been used to successfully determine optimal solutions efficiently and has proven to be more effective than other popular metaheuristic algorithms, such as Particle Swarm Optimization and Genetic Algorithm. Thus, this paper provides a comprehensive review of applications using FPA, to successfully determine optimal results to nondeterministic polynomial-time hard problems in electrical power systems. In addition, modifications of FPA to improve its performance have also been highlighted, with a review of FPAs applications in other fields.

IEEE Access

The use of metaheuristic, nature inspired algorithms for solving complex optimization problems wi... more The use of metaheuristic, nature inspired algorithms for solving complex optimization problems with non-linearity and multimodality, has become a popular tool in the field of science and engineering. Presently, there has been much development of such tools, with academics creating new natureinspired algorithms that could potentially be more efficient and effective. One such algorithm is the Flower Pollination Algorithm (FPA) developed by Xin-She Yang in 2012. This metaheuristic algorithm is modelled after the evolutionary process of flowering plants and has been useful in many fields of science and engineering, particularly electrical Power Systems, which forms the basis for modern day life and is responsible for meeting worldwide needs for reliable generation, transmission, and distribution of power. With the rapid expansion of industries and population growth, power utilities are faced with the arduous task of satisfying these needs. In addition, utilities are met with common problems, such as economic load dispatch, power quality improvement etc. To assist in solving these problems, FPA has been used to successfully determine optimal solutions efficiently and has proven to be more effective than other popular metaheuristic algorithms, such as Particle Swarm Optimization and Genetic Algorithm. Thus, this paper provides a comprehensive review of applications using FPA, to successfully determine optimal results to nondeterministic polynomial-time hard problems in electrical power systems. In addition, modifications of FPA to improve its performance have also been highlighted, with a review of FPAs applications in other fields.