Modern Optimisation - Modern Optimisation Report
Learning Outcomes
1. Critically evaluate different optimisation techniques for suitability to a given optimisation problem.
2. Apply, compare and numerically validate optimisation methods using modern relevant tools.
3. Professionally report results by giving their details and evaluating their significance.
4. Critically review recent trends in optimisation literature.
For this assignment, you are required to use either python or R to implement three modern techniques in any chosen area (chose - Vehicle Routing Protocol). However, you can change it if you think it is easier for you.
The problem is to be solved by each of the 3 techniques 30 time and then compare the techniques by taking the average of each one and present them in multiple graphs.
Description: The Modern Optimisation Report comprises of two deliverables, namely, Assessment 1.1 and Assessment 1.2.
The rationale of the overall assessment is to check whether the students can identify challenging problems (either theoretical or practical in their nature) from the domain of optimisation, critique various optimisation methods as to how they suit these problems, justify their choice of optimisation methods in the light of previous research and practice, compare the performance of various optimisation methods via rigorous statistical tests, provide intuitive or theoretical justification of the numerical performances, and report the overall argument using excellent standards of writing that are highly demanded in a work environment. The students must complete the following activities to attempt the overall assessment.
• Students will arrange themselves into groups of upto a maximum size of 4. Each student group will select a problem domain, be it applied (e.g. business, medical, or engineering) or theoretical (classical problems from literature on optimisation). Students should discuss their group formation and problem domain with the module tutors prior to submitting the same on Moodle.
• Each student will identify a unique, and acceptably challenging problem instance; the student must consult their module tutor(s) in person to obtain their consent.
o The source of problem should be public; otherwise, the student must sufficiently disclose the problem when submitting it at Moodle.
• After agreeing with the tutor(s), each student will submit their problem instance (Moodle submission by 11:59 PM Thursday, teaching week 7).
• Each student will submit Assessment 1.1 as a written report as detailed in Additional Information below.
• Students will get feedback on Assessment 1.1 by the given deadline.
• Each student must show their developing work for Assessment 1.2 to module tutors during lecture sessions and submit a draft version.
Attachment:- Modern Optimisation Report.rar