This paper describes the implementation of the Tabu Search (TS) algorithm in concert with the Computer-Aided Molecular Design (CAMD) scheme. Although other optimization approaches have been applied to CAMD with properties predicted using group contribution techniques, the TS algorithm implemented with novel neighbor-generating operators and combined with property prediction via connectivity index-based correlations provides a powerful technique for generating lists of near-optimal molecular candidates for a given application. In addition, the tabu lists help TS search the solution space both in a diversified way, to cover the entire search space, and in an intensified manner, to locate the final solution precisely. Moreover, TS is able to locate a large number of near optimal solutions within a short time.
