Showing papers by "Zong Woo Geem published in 2008"
TL;DR: This study proposes a novel derivative for discrete design variables based on a harmony search algorithm and shows how this new stochastic derivative works in the bench-mark function and fluid-transport network design.
280 citations
01 Jan 2008
TL;DR: In this chapter, the recently-developed music-inspired harmony search (HS) algorithm is introduced and its various industrial applications are reviewed.
Abstract: In this chapter, the recently-developed music-inspired harmony search (HS) algorithm is introduced and its various industrial applications are reviewed.
51 citations
01 Nov 2008
TL;DR: The harmony search is a music-inspired evolutionary algorithm, mimicking the improvisation process of music players, with theoretical background of stochastic derivative.
Abstract: The harmony search (HS) is a music-inspired evolutionary algorithm, mimicking the improvisation process of music players (Geem et al., 2001). The HS is simple in concept, few in parameters, and easy in implementation, with theoretical background of stochastic derivative (Geem, 2007a). The algorithm was originally developed for discrete optimization and later expanded for continuous optimization (Lee & Geem, 2005). The following pseudo code describes how the HS algorithm works: procedure HS // initialize initiate parameters initialize the harmony memory //main loop while (not_termination) for I = 1 to number of decision variables (N) do R1 = uniform random number between 0 and 1 if (R1 < P
31 citations
24 Mar 2008
TL;DR: An improved harmony search (HS) algorithm was applied to a natural reserve selection problem for preserving species and their habitats and found better solutions than those of another meta-heuristic algorithm, simulated annealing.
Abstract: The music-inspired meta-heuristic algorithm, harmony search, was applied to a natural reserve selection problem for preserving species and their habitats. The problem was formulated as an optimization problem (maximal covering species problem; MCSP) to maximize covered species with minimal efforts. Then, it was solved by an improved harmony search (HS) algorithm which includes problem-specific operations. When applied to real-world problem in the state of Oregon, USA, the harmony search algorithm found better solutions than those of another meta-heuristic algorithm, simulated annealing.
25 citations
13 Mar 2008
TL;DR: This study focused on pipe diameter optimization while minimizing design cost, then compared the results of HS with those of other meta-heuristic algorithms such as genetic algorithm, simulated annealing, tabu search, ant colony algorithm, shuffled frog leaping algorithm, and cross entropy.
Abstract: During last five years, harmony search algorithm has been successfully applied to various optimization problems in civil engineering, such as structural design, vehicle routing, and environmental parameter calibration. The algorithm was also frequently applied to water network problems for layout geometry, pipe diameter, and pump switching. This study focused on pipe diameter optimization while minimizing design cost, then compared the results of HS with those of other meta-heuristic algorithms such as genetic algorithm, simulated annealing, tabu search, ant colony algorithm, shuffled frog leaping algorithm, and cross entropy. The HS performed better in terms of design cost or computing efforts. For the fair comparison, identical hydraulic coefficients were used by standard network simulator EPANET.
9 citations