1. Decision Support System for School Cricket in Sri Lanka (CricDSS)
Hansinie M. Jayathilake
Dushyanthi U. Vidanagama
Faculty of Computing
General Sir John Kotelawala Defence University

2. Presentation Outline Objectives Drawbacks of current process
High level System Architecture
Technologies Used
Available Team Selection Methods
Genetic Algorithms (GA) for Team Selection
Evaluation and Suggestions
Limitations and Recommendations
Conclusion and Future Work

3. Drawbacks of Current Process
Tournament scheduling problems
Match score entering card updating problems
Communicating with SLC after a match
Invisibility of player performance time to time
Selecting the right team for the tournament

4. Objectives
Upgrade the Sri Lankan school cricket with the blend of information technology
Introducing a web based system (CricDSS) to solve the issues regarding school cricket match management and analysis.
Introducing Genetic Algorithm based advanced team selection model in line with the web solution to enhance the decision making.

5. High level System Architecture

6. Technologies Used JavaEE Netbeans IDE Glassfish web server
MySQL Database server
Hibernate ORM
Java RMI/Ajax
JGAP Framework for GA implementation

7. Available Team Selection Methods
Selection of multi-functional teams based on quality function deployment (QFD) and analytic hierarchy process (AHP)
Heuristic algorithms
Axiomatic design principles - selected based on the required skills and preparing a skill development procedure
Fuzzy set theory - selection of project teams, audit teams and worker teams
Fuzzy Inference System (FIS)- Player selection and team formation
Neural Networks - Applied to forecast the cricketer’s near term performance

8. Genetic Algorithms for Team Selection
Cricket team selection is an optimization problem which looks for the best combination of players
Evolutionary algorithms such as GA can be used for optimization of real world problems.
Less complex, more straightforward and flexible
Chromosome approach
Used to handle multiple solution search spaces
Easier to be transferred and applied in different platforms
Integer variables are easier to accommodate in GA than continuous variables
GA is less complex and more straightforward compared to other algorithms. In addition, Genetic algorithms are easier to be transferred and applied in different platforms, thereby increasing its flexibility [21]. Also unlike other solution methods, integer variables are easier to accommodate in GA than continuous variables [22].

9. How GA Works? Current players’ data Initial selection of chromosomes
Fitness function
Selection
Crossover
Mutation
Evaluate new chromosomes
Update
Termination Condition (Fitness Value)
Output
How GA Works? Y N

10. Fitness Function Implementation
One chromosome = team with 15 players
Let Overall Average Performance (Pi) of i th player for the opponent team denoted as:
(Pi) = i th player (Batting average + Bowling average + Fielding average)
Fitness of the ith player: F(Pi) = (Pi)
Fitness of a k th chromosome: F (Ck) = ∑ F (Pi) 15
i =1

11. Crossover P1 = n P2 = n +2 C1 C2 P1 1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15
P1 = n P1 1 P2 P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15
P2 = n +2 P1 1 P2 P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15 C1 P1 1 P2 P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15 C2

12. Mutation Before After P1 1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15
Before P1 1 P2 P3 P4 P5 P6 P7 P8 P9
P10
P11
P12
P13
P14
P15
After

13. Evaluation and Suggestions
All critical features of the system were tested with Coachers and School Cricket Officers
Test execution procedure was started by distinguishing the CricDSS components and features that need to be tested
It was identified that the administrator dashboard was horizontal resulting user confusion.
Also they suggested the match scheduling function needed to be more visible.

14. Limitations and Recommendations
Less accessibility to Internet by the schools in rural areas of Sri Lanka.
Only statistical data of the players are used in model creation
Usage of Glassfish server to host the application.
Also the score values of players in the database have to regularly update in order to give the correct result from the genetic algorithm.
It is highly recommended to host or deploy this application in Glassfish server since it is the most advanced server which can support for all the features and technologies in CricDSS.

15. Conclusion and Future Work
Use of open source technologies results in making CricDSS an affordable product for Sri Lankan schools.
More work on training people in remote areas where computer literacy is low.
Adaptation to mobile devices
Explore more technologies to build GA implementation in mobile devices.

16. Thank You