Module Title:   Design Optimisation

Module Credit:   10

Module Code:   ENG4029M

Academic Year:   2015/6

Teaching Period:   Semester 1

Module Occurrence:   A

Module Level:   FHEQ Level 7

Module Type:   Standard module

Provider:   Engineering

Related Department/Subject Area:   School of Engineering

Principal Co-ordinator:   Prof AS Wood

Additional Tutor(s):   -

Prerequisite(s):   ENG2027M     ENG2028M

Corequisite(s):   None

Aims:
To establish an appreciation for the role of optimisation in modern engineering practice and to provide evidence for the premise that optimisation is one component of an integrated tool kit (that includes analytical, simulation, and statistical methodologies met at earlier FHEQs) for addressing and evaluating multiple solutions to a variety of engineering-based problems.

Learning Teaching & Assessment Strategy:
Knowledge (theory, calculation/implementation methodology, application, critical analysis) is disseminated in lectures, case studies, and directed study, with practice and both general and specific (chemical, civil, electrical, industrial, mechanical, medical) engineering application/context being established in exercise classes.
Application of methodological skills are taught and practiced in computer laboratory sessions.
Oral feedback is given during computer laboratory sessions and exercise classes. Written feedback (generic and individual) will be provided via returned in-session assessment (coursework / SEM 1).
The assessment diet reflects module content and summative requirements:
A. Mathematical discipline skills are assessed in a class test (supports written feedback);
B. Engineering application and methodological skills are assessed in a problem-solving and report based coursework (supports written feedback);
C. The wider learning outcomes of the module are assessed in a final closed-book examination.

Lectures:   14.00          Directed Study:   74.50           
Seminars/Tutorials:   6.00          Other:   0.00           
Laboratory/Practical:   4.00          Formal Exams:   1.50          Total:   100.00

On successful completion of this module you will be able to...

critically evaluate the fundamental concepts of design optimization and select, implement and assess a range of appropriate optimization techniques;

On successful completion of this module you will be able to...

formulate and solve an optimization problem related to engineering design;

On successful completion of this module you will be able to...

collate and manage data, and apply scientific method, IT skills and complex systematic problem-solving strategies.

  Examination - closed book 1.50 60%
 
  Examination - closed book
  Coursework   40%
 
  Selection of DO problems set in engineering contexts-formulation, numerical solution and interpretation
  Examination - closed book 2.00 100%
 
  Supplementary Assessment - two questions to permit additional assessment of coursework Learning Outcomes

Outline Syllabus:
Formulation: translating descriptive (semantic) engineering design problems into mathematical optimisation problems, design variables, objective function, linear/non-linear mathematical programming, constrained and unconstrained problems, formulating constraints imposed on engineering system behaviour. Global/local optima. Kuhn-Tucker optimality conditions. Classification of optimisation problems.
Numerical optimisation: iterative techniques (local/global 1D, unconstrained multi-parameter, general constrained). Penalty function methods, random search, bio-inspired techniques (genetic algorithms, particle swarm).
Multi-objective problems: pareto optimum solutions.
Approximation techniques: global and local approximations used with numerical analysis of an engineering system.
Multi-disciplinary optimisation: AAO, CO, ATC

Version No:  5