The presented procedure combines continuous simulated annealing (CSA) heuristic optimization with BIOPLUME II simulation for optimizing in-situ bioremediation system design. The design goal is to minimize the total cost of facility installation and operation needed to achieve contaminant plume containment and cleanup. System design elements include pumping rates and well locations. During optimization, pumping rates are treated as continuous variables, differing from previously reported simulated annealing combinatorial optimization for groundwater management. To improve computation efficiency, CSA annealing schedules employing four different temperature update functions (TUF) are contrasted. Each yields somewhat different optimal designs and requires different computation effort. An adaptive TUF used almost 4,000 simulations to develop the lowest-cost design. A geometric TUF used 5% fewer simulations to create a design costing about 3% more. Site characteristics significantly affect optimal system design features. For a specific design, bioremediation improves with increasing hydraulic conductivity, longitudinal dispersivity, and remediation period and with decreasing retardation factor.