Operations Research and Computational Analytics in Air Transport Operations

课程简介

/ Indicative Syllabus Convexity – affine and convex sets; hyperplanes; convex functions and its properties; conjugate function, quasiconvex functions, log-concave and log- convex functions; convexity with respect to generalised inequalities. Linear programming and convex optimisation problem – Basic properties of linear programme; fundamental theorem of linear programming; simplex method; duality and the duality theorem; sensitivity and complementary slackness. Constrained minimisation/maximisation – hyperplanes; extreme points; primal methods, dual and cutting plane methods; primal-dual methods. Air transport operations and its application – Convex optimisation and optimisation methods in aviation engineering problems; critical path method and resource planning in air transport operations; air logistics transportation problem and optimisation; exact methods, heuristics; and computational analytics methods and the applications in air transport engineering. -- 1 of 3 --

目标

This subject will provide students with 1. The theory, techniques of operations research, convex optimisation, resource planning and capacity constraints modelling in aviation; 2. The knowledge to solve the operations research problem using commercial solvers; and 3. The ability to analyse numerical results to produce sensible and actionable insight and strategies.

先修要求

/ Co-requisite/ Exclusion Pre-requisite: AAE2004 Introduction to Aviation System and Air Transport Regulation

Teaching Pattern

Methodology Teaching is conducted through class lectures and laboratory. The basic knowledge, research methodology and theoretical models will be introduced. The understanding of how to address and formulate problems by using mathematical programming, operations research (OR) and optimisation algorithms techniques with modern programming language is emphasised. Research methodology, data analytics skills, algorithm design skills and programme methods are taught in class as well as the related real-life scenarios. Teaching/Learning Methodology Intended subject learning outcomes to be covered a b c d 1. Lecture     2. Laboratory     3.