Vol. 8, Issue 2 (2019)

Author(s):
Dr. Meenu Chawla

Abstract:
Mathematical optimization techniques stand as the cornerstone of problem-solving methodologies across diverse domains. This research paper provides a meticulous exploration of various mathematical optimization techniques, elucidating their fundamental principles, applications, and advancements. By synthesizing insights from seminal literature and contemporary research, this study unveils the multifaceted landscape of optimization methodologies, ranging from classical methods to cutting-edge algorithms such as genetic algorithms, simulated annealing, and particle swarm optimization. Through critical analysis and comparative evaluations, this paper elucidates the strengths, limitations, and potential synergies among different optimization paradigms, offering valuable guidance for researchers and practitioners navigating the intricate terrain of optimization-driven problem-solving. Moreover, it highlights emerging trends, challenges, and future directions in the realm of mathematical optimization, propelling the discourse towards innovative solutions and transformative advancements.