Critically evaluate the difference between deterministic search problem and stochastic search problem and how to formulate them?[5 marks]
b. Why can this problem be considered an optimisation problem? [5 marks]
Part-2: Evolutionary Algorithms [50 Marks]
2.1 Critically discuss how this assignment problem can be solved using genetic algorithms (GAs).[5 marks]
2.2 Using GAs to solve this problem, theoretically design a technical solution (providing technical details) by describing the following (discussion should be specifically for this problem) [25 marks]:
a. the fitness function and how it meets the criteria (5 marks)
b. the encoding of the chromosomes (5 marks)
c. the crossover operator (5 marks)
d. the mutation operator (5 marks)
e. the selection operator and selection pressure (5 marks)
2.3 Implement Python code with comments by using off-the-shelf (and provide the reference) or adapting the code given in the lab and run your simulation to find the employee-task assignment that produces the best (final) score [that should be indicated too]. Please make sure to submit your code. [15 marks]
2.4 In your report, critically discuss the outcome of your simulation, present statistical analysis and discuss how the algorithm evolved the solutions to obtain that final score. [5 marks]
Part-3: Swarm Optimisation Algorithms [40 Marks]
3.1 Critically discuss how can this problem be modelled using a particle swarm optimisation(PSO).
Discuss the details and justify your choices of control parameters. [10 marks]
3.2 Do we need to change the structure of the PSO algorithm as presented during the lecture to solve this problem? If so, how? [10 marks]
3.3 Critically discuss how can you implement a whale optimisation algorithm(WOA) for this problem. Discuss the details and justify your choices of the control parameters. [10 marks]
3.4 Do we need to change the structure of the WOA as presented during the lecture to solve this problem? If so, how?[10 marks]
DELIVERABLES
1.
