In-situ bioremediation of groundwater is relatively low cost and has high efficiency in remediating groundwater contaminated with petroleum hydrocarbons under suitable hydrogeologic settings. This work develops a multiobjective simulation-optimization (S-O) model for the design of an in-situ bioremediation system for petroleum-hydrocarbon contaminated groundwater. Minimizing the cost of the remediation system (installation and operation) and maximizing its reliability are the two objectives of the developed S-O model. The BIO PLUME II software simulates the remediation process and the non-dominated sorting genetic algorithm (NSGA) II optimizes remediation. The reliability objective measures the effect of uncertainty in the estimate of the initial contaminant concentration on the performance of bioremediation design, and is evaluated under five scenarios of initial contaminant concentration in an example case study illustrating this paper’s methodology. The S-O model for optimal remedation calculates Pareto fronts reflecting the best tradeoff between cost and system reliability that can be obtained. Remediation managers choose remediation strategies from the calculated Pareto front that best serve their cost preferences and remediation requirements. The calculated remediation demonstrates the effectiveness of the remediation system is sensitive to the magnitude of the initial contaminant concentration.

在适当的水文地质条件下，地下水的原位生物修复成本相对较低，并且在修复被石油烃污染的地下水方面具有很高的效率。这项工作开发了一个多目标模拟优化（SO）模型，用于设计石油-烃污染的地下水的原位生物修复系统。最小化修复系统（安装和运行）的成本并使其可靠性最大化是已开发的SO模型的两个目标。BIO PLUME II软件模拟了补救过程，非主导分类遗传算法（NSGA）II优化了补救。可靠性目标用于衡量初始污染物浓度估算中的不确定性对生物修复设计性能的影响，并在示例案例研究中的五个初始污染物浓度情景下进行了评估，以说明本文的方法。用于最佳补救的SO模型计算了Pareto前沿，反映了可以在成本和系统可靠性之间取得的最佳折衷。补救管理者从计算出的Pareto前沿中选择最能满足其成本偏好和补救要求的补救策略。计算出的补救措施表明，补救系统的有效性对初始污染物浓度的大小敏感。补救管理者从计算出的Pareto前沿中选择最能满足其成本偏好和补救要求的补救策略。计算出的补救措施表明，补救系统的有效性对初始污染物浓度的大小敏感。补救管理者从计算出的Pareto前沿中选择最能满足其成本偏好和补救要求的补救策略。计算出的补救措施表明，补救系统的有效性对初始污染物浓度的大小敏感。