Introduction to optimization
Shilpa Srivastava, Aprna Tripathi, Sulabh Bansal, Prem Prakash Vuppuluri
Abstract
A key idea in computer science, engineering, economics, and mathematics is optimization, which seeks to identify the optimal option from a range of workable options. An overview of optimization, its importance, and its many uses are given in this chapter. It highlights various forms of optimization, such as linear, nonlinear, convex, and combinatorial optimization, and examines the fundamental concepts of optimization, such as objective functions, constraints, and viable regions. In addition to contemporary strategies such as evolutionary algorithms, machine learning-based optimization, and metaheuristic techniques like genetic algorithms and simulated annealing, the chapter explores few traditional optimization techniques. Real-world applications in banking, logistics, AI, and industrial process optimization are also covered. This chapter offers insights into issue formulation, solution approaches, and efficiency concerns, with a focus on both theoretical underpinnings and real-world applications. It also presents important optimization tools and software that are frequently used in both industry and academics. By the end of this chapter, readers will have a basic understanding of optimization concepts that will allow them to use these ideas to effectively tackle challenging issues.