Table of Contents - Optimisation of JSS using GA

ABSTRACT
INTRODUCTION
JOB SHOP SCHEDULING

• Description of Job Shop Scheduling
• Assumptions in static JSSP
• Johnson’s Rule
• Algorithm of Johnson’s Rule
• Illustration for Johnson’s rule
• Modified Johnson’s Rule for n x m JSSP
• Limitations of Johnson’s Rule
• What makes scheduling problems hard?

SEARCH METHODS AND OPTIMIZATION TECHNIQUES

• Some Optimizations methods
• Branch and bound Method
• Critical Path Method
• Hill climbing
• Simplex algorithm
• Tabu Search
• Greedy Algorithm
• Simulated annealing
• Local Search

Genetic Algorithm

• Darwin’s Theory of Natural Selection
• Mechanism of GA
• Evolutionary Steps of Genetic Programming
• Characteristics of GA
• Strengths of GA
• Weakness of GA
• Applications of Genetic Algorithms
• How it differs from other optimization techniques?
• History of Genetic Algorithm

BIOLOGICAL BACKGROUND

• Operational Parameters of Genetic Algorithm
• Chromosomes
• Fitness
• Selection
• Genetic Operators
• Crossover
• Mutation
• Termination

IMPLEMENTATION OF GA TO JSSP

OUR APPROACH TO JSSP USING GA

RESULTS AND CONCLUSIONS

REFERENCES
© 2006 Kumaravel & Project Team