Advancements in Quantum-PSO and Its Application in Sustainable Development

Abstract

Optimization is an inevitable part of sustainable development. Optimization techniques are employed to improve sustainability and achieve the goals of sustainable development. Quantum inspired Particle Swarm Optimization (QPSO) is a probabilistic optimization algorithm based on the quantum mechanics and trajectory analysis of PSO. Quantum mechanics provides a system of uncertainty letting the particle appear anywhere in the feasible space with certain probability. Further, QPSO has only one parameter that controls creativity and imagination of particles during evolution making it easy to control. Because of ease to control and global searching ability, QPSO has gained popularity among researchers who have contributed a lot in finding its application in sustainable development in varied domains as well as suggesting strategies for the improvements in its performance. This paper provides an integrated and synthesized overview of the advancements in QPSO algorithm since its advent. A state-of-the-art snapshot of different improvement strategies categorized according to the adapted method and a review of the QPSO algorithms used in sustainable development related to social, economical, environmental, and energy resources sustainability has been presented. Aim is to provide the researchers a platform for development of efficient QPSO based algorithms suitable for different real-life optimization problems.