A New Heuristic Optimization Algorithm: Harmony Search

TLDR

Optimization problems across many fields have traditionally been addressed by linear programming, nonlinear programming, and dynamic programming, but their limitations have spurred interest in heuristic approaches inspired by natural or artificial phenomena. This paper proposes Harmony Search, a new heuristic algorithm that mimics the improvisation process of music players. The algorithm’s effectiveness is demonstrated on a traveling salesman problem and a least‑cost pipe network design problem.

Abstract

Many optimization problems in various fields have been solved using diverse optimization al gorithms. Traditional optimization techniques such as linear programming (LP), non-linear programming (NLP), and dynamic program ming (DP) have had major roles in solving these problems. However, their drawbacks generate demand for other types of algorithms, such as heuristic optimization approaches (simulated annealing, tabu search, and evolutionary algo rithms). However, there are still some possibili ties of devising new heuristic algorithms based on analogies with natural or artificial phenom ena. A new heuristic algorithm, mimicking the improvisation of music players, has been devel oped and named Harmony Search (HS). The performance of the algorithm is illustrated with a traveling salesman problem (TSP), a specific academic optimization problem, and a least-cost pipe network design problem.