CS607 Artificial Intelligence Assignment No. 02 Fall December 2014

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CS607 Artificial Intelligence Assignment No. 02 Fall 2014 Solution & Discussion Due Date: December 10, 2014

1) You should consult recommended books to clarify your concepts as handouts are not sufficient.

2) You are supposed to submit your assignment in .doc format. Any other formats like scan images, PDF, Zip, rar, bmp, docx etc will not be accepted

3) You are advised to upload your assignment at least two days before Due date.

4) This assignment file comprises of Three (03) pages.

5) Assignment is non graded and will not contribute any marks in final grades



Important Note:

Assignment comprises of 20 Marks. Note that no assignment will be accepted after due date via email in any case (whether it is the case of load shedding or emergency electric failure or internet malfunctioning etc.). Hence, refrain from uploading assignment in the last hour of the deadline, and try to upload Solutions at least 02 days before the deadline to avoid inconvenience later on.


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Note that there is fluctuation in purchase rate of the same product in different transactions (e.g. in transactions T1 and T3, same amount of products were purchased but due to different purchase rates, total amount paid was different). Each transaction can be represented by a linear equation as follows:

QAiRAi+ QBiRBi+ QCiRCi+ QDiRDi =Total-Costi

Where QAi is quantity of product-A in ith transaction. Here i = {1, 2…10}

RAi is purchase rate of product-A in ith transaction

And

Total-Costi = Total cost spent in ith transaction.

Your task is to find the purchase rate of every product. One way to solve such problem is by using system of linear equations and finding the unknown variable (recall your Calculus concepts) but we cannot use this method here (guess why?). In fact, we have to find average (approx) purchase rate of each product that can best satisfy above transactions.

Genetic Algorithm (GA) can be a help in this case. As you have studied about GA in this course, so your task is to devise a solution using GA (that shall result in finding the optimal purchase rate of each product) by answering the following questions.

Questions

Q. No. 1: Describe your Chromosome structure / solution encoding scheme. How it will represent initial and intermediate solutions?

Q. No. 2: Describe your Fitness function for the given problem. How it will calculate fitness value of intermediate solutions.

Q. No. 3: Describe your strategy for Crossover operation. How intermediate solutions will generate new solutions?

Q. No. 4: Describe your strategy for Mutation operation. How newly generated solutions will be mutated?

Q. No. 5: Describe your Stopping condition. How you choose to stop/terminate execution of your GA?