Multiobjective Pump Scheduling Optimization Using Harmony Search Algorithm (HSA) and Polyphonic HSA

• Published in: Water resources management 2013-03, Vol.27 (5), p.1249-1261
• Main Authors: Kougias, Ioannis P., Theodossiou, Nicolaos P.
• Format: Article
• Language: English
• Subjects: Algorithms; Atmospheric Sciences; Civil Engineering; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Electric power; Environment; Exact sciences and technology; Geotechnical Engineering & Applied Earth Sciences; Harmony (Music); Hydrogeology; Hydrology. Hydrogeology; Hydrology/Water Resources; Maintenance costs; Marketing; Methods; Molybdenum; Music; Objectives; Optimization; Optimization techniques; Peak demand; Pumps; Scheduling; Search algorithms; Studies; Water management; Water resources; Water resources management; Water supply; Water treatment
• ISSN: 0920-4741; 1573-1650
• DOI: 10.1007/s11269-012-0236-5

Harmony Search Algorithm (HSA) is a metaheuristic method that has attracted the scientific interest since its first presentation in 2001. It is a music inspired method, imitating the music creation process in order to find optimal solutions in complicated problems. HSA’s successful application on single – objective optimization problems has resulted to an increasing interest in the implementation of HSA towards multiobjective optimization. The authors have adjusted HSA in order to deal successfully with multi-criteria water management problems. This adjustment has resulted to the creation of Multiobjective – HSA (MO-HSA). In addition, they have designed the multiobjective variant Polyphonic-HSA (Poly-HSA), which is inspired by the independent development of different voices in music and borrows elements from Swarm Intelligence and the single-objective variant Global-Best HSA. In the first part of this paper, both methods are presented in detail. Moreover, the performance of the proposed Algorithms is evaluated using standard multiobjective test – functions. ZDT and DTLZ multiobjective tests have been chosen and indicators such as Hypervolume, C – metric and diversity metric – Δ have been used to measure the convergence to the optimal front and the diversity of the solutions obtained by the proposed methods. In the second part, MO-HSA and Poly-HSA have been introduced towards the optimization of a pump scheduling problem. The objectives considered are water supply, pumping cost, electric power peak demand and pump maintenance cost. Both methods converged to non-dominated fronts and provided excellent results which are presented in 3d figures, indicating that these methods can be effectively used in multiobjective water management problems.