Bioremediation studies were carried out for the treatment of Cr(VI) bearing sludge using indigenous microorganisms isolated from a chromium contaminated site. Effects of moisture content, initial substrate and biomass concentrations on the bioremediation process were studied by conducting batch and continuous experiments. The leachability of total chromium and Cr(VI) from remediated soil was evaluated and compared with that of untreated soil. Experimental data was used to determine biokinetic parameters and validate a mathematical model. Single objective and multi-objective management models were developed by embedding the mathematical model describing the process in a simulation-optimization framework. Single objective management models considered either cost minimization or minimization of time for treatment. Genetic Algorithm, available in MATLAB tool box was used for solving the optimization problems. Applicability of proposed management models was demonstrated for the remediation of Cr(VI) bearing sludge in Ranipet, Tamilnadu, India. Multi-objective management model was used to derive the Pareto-optimal front, which describes the trade off between the cost of treatment and the time taken for treatment. © 2010 Elsevier B.V.