APPLICATION OF HARMONY SEARCH TO MULTI-OBJECTIVE OPTIMIZATION FOR SATELLITE HEAT PIPE DESIGN

multiple objectives such as performance, reliability, and weight. To consider these objectives simultaneously, multi-objective optimization can be considered. In this study, a new multi-objective method considering both thermal conductance and heat pipe mass is introduced. This method has two steps: At first, each single objective function is optimized; then multi-objective function, which is the sum of individual error between current function value and optimal value in terms of single objective, is minimized. Here, the multi-objective function, representing thermal conductance and heat pipe mass, has five design parameters such as length of conduction fin, cutting length of adhesive attached area, thickness of fin, adhesive thickness, and operation temperature of the heat pipe. Study results showed t h a t t h e a p p r o a c h using recently-developed meta-heuristic algorithm, harmony search, found better solution than traditional calculus-based algorithm, BFGS. I. META-HEURISTIC ALGORITHM: HARMONY SEARCH ARMONY SEARCH (HS) is a recently-developed meta-heuristic optimization algorithm mimicking music improvisation [1], where each musician corresponds to each decision variable in optimization; pitch range of each music instrument corresponds to value range of each variable; and each harmony improvised corresponds to each solution vector. Just as musicians polish better harmonies practice a f t e r practice, the HS algorithm polishes better vectors iteration after iteration. The HS algorithm has been applied to various real world optimization problems. Geem et al. [2] and Geem [3] applied harmony search to optimal design of water distribution networks. The HS model found less or equal design solutions when compared to other meta-heuristic algorithms such as genetic algorithm (GA), simulated annealing (SA), and tabu search (TS). For the optimal expansion design of water distribution network in New York City, while mathematical method (LP and DP) found a solution of $78.09 million and GA found a solution of $37.13 million (after 1,000,000 function evaluations), HS found a solution of $36.66 million (6,000 evaluations). Geem [4] applied HS to optimal pump switching for the serial pumping system. While GA found a solution of 11263.19 (HP, horse power), HS found a solution of 11169.43 HP, which is also better than popular mathematical technique (B&B). The HS (19 seconds) computed much faster than B&B (28 minutes). Lee and Geem [5] and Lee et al. [6] applied HS to the structural designs such as electricity transmission truss as shown in Figure 1. 75 in. 100 in.