Covers the formulation and problem definition in optimization, focusing on defining the objective function, constraints, and feasible set.
Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.
Covers the derivation and application of Euler-Lagrange equations for optimization problems in mathematical analysis.
Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.
Explores optimization methods in engineering, covering decision variables, constraints, and various solving techniques.
Covers the general framework of optimization and simulation, including deterministic control and the optimization problem.
