Suppose there are k 1 (k 1 ≥ 1) test treatments that we wish to compare with k 2 (k 2 ≥ 1) control treatments. Assume that the observations from the ith test treatment and the jth control treatment follow a two-parameter exponential distribution $${E\left({\xi_i ,\theta}\right)}$$ and $${E\left({\eta_j ,\theta}\right)}$$ , where θ is a common scale parameter and $${{\xi_i }}$$ and $${{\eta_j}}$$ are the location parameters of the ith test and the jth control treatment, respectively, i = 1, . . . ,k 1; j = 1, . . . ,k 2. In this paper, simultaneous one-sided and two-sided confidence intervals are proposed for all k 1 k 2 differences between the test treatment location and control treatment location parameters, namely $${\xi_i -\eta_j ,i=1,\ldots,k_1; j=1,\ldots,k_2}$$ , and the required critical points are provided. Discussions of multiple comparisons of all test treatments with the best control treatment and an optimal sample size allocation are given. Finally, it is shown that the critical points obtained can be used to construct simultaneous confidence intervals for Pareto distribution location parameters.