Optimization with Python: all you need for LP-MILP-NLP-MINLP
Operational planning and long term planning for companies are more complex in recent years. Information change fast, and the decision making is a hard task. Therefore, optimization algorithms are used to find optimal solutions for these problems. Professionals in this field are the most valued ones. In this course you will learn what is necessary to solve problems applying: Linear Programming ( LP ) Mixed-Integer Linear Programming ( MILP ) NonLinear Programming ( NLP ) Mixed-Integer Linear Programming ( MINLP ) Genetic Algorithm ( GA ) Particle Swarm ( PSO ) Constraint Programming ( CP ) Second-Order Cone Programming ( SCOP ) NonConvex Quadratic Programmin ( QP ) The following solvers and frameworks will be explored: Solvers : CPLEX – Gurobi – GLPK – CBC – IPOPT – Couenne – SCIP Frameworks : Pyomo – Or-Tools – PuLP Same Packages and tools : Geneticalgorithm – Pyswarm – Numpy – Pandas – MatplotLib – Spyder – Jupyter Notebook Moreover, you will learning how to apply some line...