What is a jaya algorithm in C and how is it implemented?

Table of Contents

• Introduction
• Working Principle
  • Key Concepts
  • Mechanism
• Implementation in C
• Explanation
  • Initialization
  • Evaluation
  • Update Mechanism
  • Termination
• Conclusion

Introduction

The Jaya algorithm is a metaheuristic optimization algorithm introduced by R. Venkata Rao in 2016. It aims to find the optimal solution by focusing on the best and worst solutions in the population. Known for its simplicity and efficiency, the Jaya algorithm has been applied to various optimization problems.

Working Principle

Key Concepts

1. Best Solution: The algorithm tracks the best solution found so far.
2. Worst Solution: It also considers the worst solution in the population.
3. Update Mechanism: Solutions are updated based on their distance from the best and worst solutions.

Mechanism

1. Initialization: Begin with a randomly initialized population of solutions.
2. Evaluation: Assess the fitness of each solution.
3. Update: Modify each solution based on the best and worst solutions.
4. Termination: Continue updating until the stopping criteria are met.

Implementation in C

Here is a basic implementation of the Jaya algorithm in C:

Explanation

Initialization

The population is initialized with random solutions within the defined bounds.

Evaluation

The fitness of each solution is evaluated using the objective function.

Update Mechanism

Each solution is updated based on its distance from the best and worst solutions in the population.

Termination

The algorithm iterates until the maximum number of iterations is reached.

Conclusion

The Jaya algorithm is an efficient optimization technique that focuses on both the best and worst solutions in the population. Its simplicity and effectiveness make it a useful tool for various optimization problems. The provided C implementation demonstrates how to apply the Jaya algorithm to find optimal solutions.