In this paper. tabu search (TS), a universal heuristic method besides simulated annealing (SA) and genetic algorithms (GAs) that effectively overcome local optimum, is adapted to the optimal design problem of multiproduct batch chemical processes successfully. A novel concept of double tabu list is proposed. and the comparison between customized (proposed) algorithm and standard one is given, which illustrates the improvement by the use of the double tabu list. The methods of constructing dynamic neighborhood, realizing diversification and changing the step size of continuous variables adaptively are designed. An appropriate empirical equation of tabu size is obtained through computational experimentation. To demonstrate the effectiveness of TS in solving the proposed problem, four examples adopted from literature, together with the computation results, are presented. Better results are obtained in comparison with the results of mathematical programming (MP) and SA.