A novel multi-objective fuzzy model for optimization of oil sludge management by considering Health, Safety and Environment (HSE) and resiliency indicators in a gas refinery

Waste management is one of the most important factors controlling environmental pollution and safety in gas refineries. It attends to optimize cost, environmental pollution, safety, and profitability. Since oil sludge management is not an indivisible issue from in a gas refinery, it is necessary to plan the supply process including refineries, gas compressor stations and city gate stations. Existence of toxic organics and heavy metals such as lead, copper, mercury, nickel and zinc have caused oil sludge is considered as hazardous waste and its storage and disposal in public landfill sites is not permitted. The current mechanism of disposal of oil sludge in the gas refinery of this study is incorrect. This paper presents a novel mathematical model for oil sludge management in a large gas refinery. The oil sludge management methods have been studied and included in the mathematical model. The objectives of the multi-objective mathematical model is to optimize cost, HSE and resiliency factors. Due to the uncertainty of certain parameters, the model is considered by fuzzy logic and planning. The mathematical model is solved by improved epsilon constraint and the best results are obtained by using data envelopment analysis (DEA). A complete sensitivity analysis is conducted with respect to various methods and land increase. The results show that the existing uncertainty has changed the solution space in the problem. In addition, environmental impacts are reduced by maximizing economic objective function. Moreover, demand changes will change the constraints related to demand and consequently solution space and optimum Pareto solution are also changed. The results of this study are verified and validated by expert judgments at the refinery. It is shown that the unique integrated mathematical approach of this study will respectively result in 19 and 12 percent improvement in environmental cost and safety factors. This is the first study that presents and integrated epsilon constraint and DEA approach for sludge management by considering HSE and resiliency factors.