Now we need to assign a fitness value to the chromosome. Probability that crossover will occure Number of classes that is moved randomly by single mutation operation For instance, if a class starts at 1pm and lasts for three hours, it has entries in the 1pm, 2pm, and 3pm slots.Ĭopy Code // Number of crossover points of parent's class tables Each hour of a class has a separate entry in the vector, but there is only one entry per class in the hash map. There is an additional hash map which is used to obtain the first time-space slot at which a class begins (its position in vector) from the address of the class' object. The slot should be an std::list because during the execution of our algorithm, we allow multiple classes during the same time-space slot. We can use an std::vector with a size 12*5*number_of_rooms. Also, we assume that classes cannot begin before 9am, and should finish before or at 9pm (12 hours total), and working days are from Monday to Friday (5 days total). How can we represent the chromosome for a class schedule? Well, we need a slot (time-space slot) for each hour (we assume that time is in one hour granules), for every room, every day. In other words, we should be able to calculate the fitness value of our solution.
How to write c code for rm scheduling how to#
Also, we should know how to specify how good our solution is. The first thing we should consider when we deal with a genetic algorithm is how to represent our solution in such a way that it is feasible for genetic operations such as crossover and mutation. It also stores how many seats (sum of student groups' sizes) are needed in the classroom, if the class requires computers in the classroom, and the duration of the class (in hours). ClassĬourseClass holds a reference to the course to which the class belongs, a reference to the professor who teaches, and a list of student groups that attend the class. The Course class has an ID and the name of the course. IDs are generated internally and automatically.
If the classroom has computers, it is expected that there is a computer for each seat. The Room class has an ID and the name of the classroom, as well as the number of seats and information about equipment (computers). It also contains a list of classes that the group attends. The StudentsGroup class has an ID and the name of the student group, as well as the number of students (size of group). It also contains a list of classes that a professor teaches. The Professor class has an ID and the name of the professor. Let's start by explaining the objects which makes a class schedule. In this example, only hard requirements are implemented. Hard and soft requirements, of course, depend on the situation. Distribution (in time or space) of classes for student groups or professors.Some soft requirements (can be broken, but the schedule is still feasible): To place a class in a classroom, the classroom must have laboratory equipment (computers, in our case) if the class requires it.A classroom must have enough seats to accommodate all students.
In this article, I assume that you are familiar with the basic concepts of genetic algorithms, and I won't describe them in detail because it has been done so many times before. This is where genetic algorithms come in to the game. For more complex inputs and requirements, finding a considerably good solution can take a while, or it may be impossible. The problem can be solved using a heuristic search algorithm to find the optimal solution, but it only works for simple cases. Program to find GCD of two numbers in C.Making a class schedule is one of those NP hard problems.Program to print prime numbers from 1 to n.Decimal to Binary Conversion Program in C.converting entered string to Capital letters Int i,j,k,numstr,numcipher,numkey,lenkey,templen,tempkey,flag=-1,size,cipherkey,lennumstr,row1,row2,col1,col2 Int insertelementat(int position,int a,int size)
0 kommentar(er)
