To sustain water quality in water distribution system (WDS), disinfectant generally chlorine is boosted to water distribution system. However, the concentration of chlorine should be limited to acceptable scope. The upper bound of the scope is set for preventing the occurrence of disinfectant byproduct, which is harmful to human health. The lower bound of the scope is set for controlling the growth of microorganism as well as reducing the cost. As such, the optimization model was applied to solve the water quality issue in WDS. However, in WDS, chlorine decays and varies with time and space, affected by pipe material, temperature, pH value, and chlorine injection. Therefore, in this paper, an inexact \({\mathrm{m}}_{\uplambda }\) fuzzy chance-constrained programming (IMFCCP) model was proposed to optimize the chlorine injection to maintain chlorine in WDS at an acceptable level with consideration of uncertainty in water quality simulation. The results indicated that the upper bounds, the lower bounds, and intervals of the injection mass increased with preference parameter λ, which means that the results are more unreliable with higher preference parameter λ. However, the effect of reliability level ζ on the injection mass is determined by the relationship between the preference parameter λ and reliability level ζ. In case of \(\uplambda \le {\upzeta }_{\mathrm{U}}={\upzeta }_{\mathrm{L}}\), the effect is not more significant than the case of \(\uplambda >{\upzeta }_{\mathrm{U}}={\upzeta }_{\mathrm{L}}\). The results can help managers determine the injection strategy under uncertainty.

为了维持水分配系统（WDS）中的水质，通常将消毒剂中的氯提高到水分配系统中。但是，氯的浓度应限制在可接受的范围内。设定范围的上限是为了防止产生对人体健康有害的消毒副产物。范围的下限用于控制微生物的生长以及降低成本。因此，采用了优化模型来解决WDS中的水质问题。但是，在WDS中，氯会随管道材料，温度，pH值和注入的氯而衰减并随时间和空间而变化。因此，在本文中，不精确的\（{\ mathrm {m}} _ {\ uplambda} \）考虑到水质模拟的不确定性，提出了模糊机会约束规划（IMFCCP）模型来优化注氯量，以将WDS中的氯保持在可接受的水平。结果表明，注射质量的上限，下限和间隔随偏好参数λ的增加而增加，这意味着对于较高偏好参数λ的结果更加不可靠。但是，可靠性等级ζ对注射质量的影响取决于偏好参数λ和可靠性等级ζ之间的关系。对于\（\ uplambda \ le {\ upzeta} _ {\ mathrm {U}} = {\ upzeta} _ {\ mathrm {L}} \），效果不比\（\ uplambda> {\ upzeta} _ {\ mathrm {U}} = {\ upzeta} _ {\ mathrm {L}} \}）。结果可以帮助管理人员确定不确定性下的注入策略。