Time-constrained intermediate storage multiproduct batch process scheduling with uncertain processing time is concerned in this paper. The triangular fuzzy number is applied to describe the imprecise processing time of products. An approach for ranking fuzzy numbers is used to estimate the value and uncertainty of the makespan which are employed to establish the mathematical model. An improved particle swarm optimization with estimation of distribution algorithm (IPSO-EDA) is proposed. The IPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the particle swarm optimization (PSO)

and therefore each particle has comprehensive search ability. Meanwhile

the NEH-based initialization and local search are introduced to construct good initial solutions and enhance the local exploitation

respectively. In addition

the influence of parameter settings of the IPSO-EDA is investigated based on the method of factorial design. The simulation results indicate the superiority of IPSO-EDA in terms of effectiveness and efficiency.