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M E N TO R : H I R A N M AY S A M M A D A R

G R O U P M E M B E R S :

A B H I N AV K U M A R ( 1 0 3 0 1 0 )

P I Y U S H K U M A R C H A U H A N ( 1 0 3 0 0 1 )

K H U S B O O K U M A R I ( 1 0 3 0 0 2 )

A S H I S H M I S H R A ( 1 0 3 0 2 2 )

DAPARTMENT OF COMPUTER SC. & ENGG.

UNIVERSITY TIMETABLE SCHEDULING USING PARTICLE

SWARM OPTIMIZATION

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Problem definition

University timetable scheduling using particle swarm optimization

It is a NP-Hard problem and we solve this problem using

particle swarm optimization

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What is P and NP ?

P is set of problems that can be solved in polynomial time

NP (nondeterministic polynomial time) is the set of problems that can be solved in polynomial time by a nondeterministic computer

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NP-Complete Problems

We will see that NP-Complete problems are the “hardest” problems in NP:

If any one NP-Complete problem can be solved in polynomial time…

…then every NP-Complete problem can be solved in polynomial time…

…and in fact every problem in NP can be solved in polynomial time (which would show P = NP)

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What is NP-Hard ?

Definition of NP-Hard

A set of problems which is converted to a particular

problem but that particular problem is not converted

to any other problem of that set.

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Constraints

Common type of constraints:-

Time assignment

Room capacities

Number of laboratories

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Hard constraints

No student attends more than one period at the same time.Only one lecture is taking place in each room at a given

time.No teacher should be taking two classes at the same point

of time.Minimum of one laboratory assistant should be present in

each laboratory session.Minimum of two laboratories should be there in every

section of the Basic Sciences & Humanities Department.

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Soft constraints

All the laboratory sessions in a week should be scheduled in the first half.

A lecturer wants his lecture to be delivered in the last period.

Swapping of the periods.

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What is Particle Swarm Optimization ?

A simple, computationally efficient optimization method

population-based, stochastic search

based on a social-psychological model of social influence and social learning

individuals follow a very simple behavior: emulate the success of neighboring individuals

emergent behavior: discovery of optimal regions in high dimensional search spaces

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Geometrical Illustration

Position updatesxi (t + 1) = xi (t) + vi (t + 1)

Velocity update per dimension:vij (t + 1) = vij (t) + c1r1j (t)[yij (t) − xij (t)] + c2r2j (t)[ˆyj (t) − xij (t)]

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Front End

The front end is design by using core java.

The user gives the details about following :-

Number of classroomNumber of laboratoryNumber of departmentNumber of subject Number of faculty

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Back End

The back end is created with the help of DBMS.

We use the following table for creating the database.

Teacher( t_name,t_id,designation,dept,address,phno.) Subject( s_name,s_code,no._of_lecture,sem,dept) Classroom(room_id,capacity) Laboratory(lab_name, lab_id,capacity,dept_lab) Department(dname,dept_id,hod_name,no_of_lab,no._of_teacher,no_of_r

oom) Teacher(t_id,t_sub)

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Architecture of University Timetable System

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THANK YOU