|Course title||Operational Research|
|Institution||Instituto Superior Tecnico Lisboa|
|Course address||Av. Rovisco Pais, 1049-001 Lisboa, Portugal|
|Minimum year of study||3rd year|
|Minimum level of English||Good|
|Minimum level of French||None|
|Key words||Operational Research, Operations Research, Optimization, Linear Programming, Monte Carlo simulation, Queueing (Waiting Line Theory), Travelling salesman problem|
|Professor responsible||Rui Carvalho Oliveira|
Amílcar Arantes, Marta Gomes, Nuno Moreira, Rui Marques, Rui Oliveira
|Number of places||Minimum: 10, Maximum: 15, Reserved for local students: 0|
In a time of competitiveness and scarcity of raw materials, an industrial (indeed, any) system must work in a state not far from its optimum, "small" improvements being sometimes crucial for success or even survival. Operational Research (OR*) supplies specific techniques to optimize and manage, and promotes habits of analysis arising from the inspection of the system model. The central objective of OR is optimization, i.e., "to do things best under the given circumstances", to the greatest profit or smallest cost. This general concept has many applications: agricultural planning, biotechnology, distribution of goods and resources, engineering systems design, environmental management, health care management, inventory control, manpower and resource allocation, manufacturing of goods, military operations, production process control, sequencing and scheduling of tasks, telecommunications, traffic control.
Only some of the applications mentioned will be addressed in the course (see Programme below). The computer and the Internet will be indispensable tools.
*"Operations Research" in American English.
|Programme to be followed||
Introduction to Operational Research (OR): origins, methodological principles, taxonomy of OR models, application domains.
Linear Programming (LP) models: formulation and structure of LP problems; solving LP problems (basics of the SIMPLEX algorithm; use of solvers); sensitivity analysis; particular cases and formulation of LP problems (transportation, assignment, and location problems); extensions to LP.
Simulation models: random sequences generation and Monte Carlo methods; methodologies for systems analysis and model design for discrete-event simulation; simulation software packages for model implementation; design of simulation experiments and results analysis.
Queuing models: formulations and core concepts; basic queuing models (M/M/1, M/G/1 and M/M/S) and their use for decision support; complex systems and queuing networks.
Logistics and inventory control: deterministic and stochastic models; service level vs costs and optimal inventory levels.
Graphs and network models: formulations and core concepts; optimization algorithms for simple problems (shortest path, minimum spanning tree); routing problems (travelling salesman); project management and CPM/PERT.
Systems performance evaluation: basic concepts (efficiency, effectiveness, productivity); simple and aggregated performance indicators; parametric and non-parametric methodologies; Data Envelopment Analysis (DEA); benchmarking.
|Prerequisites||Basic knowledge of: Linear Algebra; Calculus; Probability & Statistics. Basic knowledge of Excel.|
|Course exam||Written exam (in the afternoon of the last day of course); open book.|