Harmony search

Harmony search (HS) is a metaheuristic algorithm (also known as soft computing algorithm or evolutionary algorithm) mimicking the improvisation process of musicians. In the process, each musician plays a note for finding a best harmony all together. Likewise, each decision variable in optimization process has a value for finding a best vector all together.

Harmony search applications
The HS algorithm had been successful in a wide variety of optimization problems in the following fields.

Bench-mark problems

 * Traveling salesman problem
 * Various mathematical functions
 * Rosenbrock's banana function
 * Six-hump camel back function

Real-world problems

 * Combined heat and power economic dispatch
 * Water distribution network design
 * Structural design
 * Vehicle routing
 * Hydrologic parameter calibration
 * Aquifer parameters and zone structures
 * Pump switching
 * Multiple dam scheduling
 * Satellite heat pipe design
 * Offshore structure mooring
 * QoS based multicast routing
 * Tour routing
 * Music composition
 * Sudoku puzzle solving

Harmony search features
HS has several advantages when compared with traditional gradient-based mathematical optimization techniques as follows:


 * HS does not require complex calculus, thus it is free from divergence.
 * HS does not require initial value settings for the decision variables, thus it may escape local optima.
 * HS can handle discrete variables as well as continuous variables, while gradient-based techniques handle continuous variables only.

Also, the HS algorithm could overcome the drawback of genetic algorithm's building block theory by considering the relationship among decision variables using its ensemble operation.

Other Related Algorithms

 * Genetic algorithms
 * Simulated annealing
 * Tabu search
 * Ant colony optimization