Mon., 16 – Introduction: Welcome: Portugal, Lisboa, IST.
Course webpage (CWP).
Linear Programming: Historical note. Model. Dantzig's simplex algorithm; matrix method; duality. Computational resolution.

Tue., 17 – Transportation Problem Model. Stepping-stone algorithm. Computational resolution.
Monte Carlo simulation: simulation (Monte Carlo method). Sampling experiments on models. Ppt "The MC method in the practice of QC" (see Portalegre). Meaning of "random". (Pseudo)random number generation. Illustr. Boston U.. Sum of uniforms, 'mc' according to Buescu (see Calcn.).
Paradox of Monty Hall. Random variable generation.
Continuous variable generation. Correction of the extrema 0 and 1. Uniform and exponential distributions.

Wed., 18 – Queueing theory: Structure of the models. Poisson arrivals, exponential servicing. Infinite and finite populations. Computational resolution. "Fish on Venus" ('mc'). Two uniform Gaussians (vs. 'mc').
Sums (central lim. theorem), products: two (or more) Gaussians, two uniforms.

Thu., 19 – Inventory management:
Obtaining the sampling plan by simulation. The Monte Carlo method in the practice of QC (.ppt). "Computing" Q by simulation. Simulation and exact calculation of the sampling plan: "Q & AS: an 'mc' method approach".ppt (Compiègne).
Travelling Salesman Problem: route optimization in cycles. Computational resolution.

Fri., 20 – Examination.

http://web.ist.utl.pt/~mcasquilho/acad/or/intro2.php Created: 1999-05-24 — Last modified: 2015-03-15