In this course outline, what needs to be done is explained in details (never mind the devision into two assignments 1.1 and 1.2, just do one whole assignment). For this assignment, you are required to use either python or R to implement 3 modern techniques in any chosen area (the one I chose is 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.

4. Critically review recent trends in optimisation literature. The report uses excellent recent and classic academic literature to justify the experimental setup, and to critically review the results achieved. The references used are extremely relevant to the problem domain and it is clearly evident that the experimental design in this report follows the state of the art or even improves upon that.

3. Professionally report results by giving their details and evaluating their significance. An excellent and critical description of significance of achieved results, alongwith a sound justification. Abstract/conclusi ons are appealing and highlight research questions, important results and important steps of experiment. The report is organised extremely well. Various sections link together with cross referencing where necessary. Sentence, paragraph and section structuring is excellent. Strong evidence of prior training in academic writing. Tables, figures, and/or sections are numbered, and captions and legends are very readable. All the tables and figures are also discussed well in the text. Essentially, the report can be extended into a research article with a reasonable effort.

2. Apply, compare and numerically validate optimisation methods using modern relevant tools. A thorough description and justification of configuration parameters. Problem data is described well and needs no further investigation. Experimental details are described well enough to replicate the experiments. If extra details are needed, they are made easily available through appendices or online repositories such as github. An excellent comparison of results where tough benchmarks that represent the state of the art are selected to improve upon. Assumptions behind the use of tests of statistical significance conducted are fulfilled.

80 – 100% 1. Critically evaluate different optimisation techniques for suitability to a given optimisation problem. Information on a valid problem domain and a corresponding problem instance are well understood from the report. Rationale given for the candidate optimisation techniques is sound. Only highly relevant and excellent scienitific literature is referenced, and the reasoning derived out of it reflects personal insight and very reasonable predictions on performance. Grammar is excellent and the standard of academic writing is excellent.

Assessment Criteria 4. Critically review recent trends in optimisation literature. 20% The report uses little to no academic literature to justify the experimental setup, and/or the results achieved. The report uses little academic literature to justify the experimental setup, and/or the results achieved The report uses little academic literature to justify the experimental setup, and/or the results achieved. The references used are not particularly relevant to the problem tried and/or may only refer to optimisation in general. The report uses some academic literature to justify the experimental setup, and/or the results achieved. The references used may be relevant to a much larger problem domain but little evidence is provided to ensure what lessons are learnt to guide the experimental design in this report.

Assessment 1.1 will have a maximum word count of 1000 excluding tables, figures and references. Assessment 1.2 will have a maximum word count of 2000 excluding tables, figures and references. ). For completion, the report for Assessment 1.2 must also include the work reported in Assesment 1.1, revised and updated according to the feedback received. Although, the content pertaining Assessment 1.1 will not count towards the maximum word count of 2000, it must blend in with the rest of the report (instead of disconnecting as in a copy-and-paste job).

The students will apply at least three variations of modern optimisation methods on an acceptably challenging problem, and report the findings in an excellent academic style. The report will be submitted as two deliverables, namely, Assesment 1.1 and Assessment 1.2. Assessment 1.1 (weightage 30%) will detail the problem domain and problem specifics chosen by the student. Also, this deliverable will justify the choice of optimisation methods to solve the selected problem. Assessment 1.2 (weightage 70%) will implement the proposals made in Assessment 1.1; the proposals must be revised as per any feedback received. The implementation should numerically compare the attempted optimisation methods