ITM 501 Lecture Notes - Lecture 1: Risk Neutral, Decision Analysis, Expected Value Of Perfect Information
11 Apr 2015
School
Department
Course
Professor
Document Summary
Monte carlo (some factors are uncertain, requires simulation) Linear programming (using lines (graph) to find optimal solution) A model is a simplified representation of a complex reality: conceptual model, mathematical, visual, physical, simulation. The transformation of a real-world managerial problem into a (mathematical) model to gain insight and find a solution o. Can be applied to many business problem areas (e. g accounting, finance, Lower costs than dealing with the real system. Lower costs and lower risks for mistakes economics, marketing, operations and logistics, etc) Can be time consuming, expensive, or not even feasible. Could result in huge errors, if the model is over simplified. Decision makers may be reluctant to accept the results/outcomes. Model development process could be challenging when the environment is uncertain. Deterministic models: all relevant data known with certainty, no randomness in decision parameters, mathematical models. Quantitative data: numerical data such as costs and revenues , or non-numeric, but easy to quantify data such as experience .
