A multi-objective model for an integrated oil and natural gas supply chain under uncertainty

The oil and gas networks are overlapped because of the inclusion associated in crude oil. This necessitates integration planning supply chain together. In recent years, hydrocarbon market has experienced high fluctuation demands prices which leads to considerable economic disruptions. Therefore, chain, considering uncertainty is a significant area research. this regard, study develops multi-objective stochastic optimization model for tactical downstream segment natural under price demand petroleum products. proposed was formulated based on two-stage programming approach with finite number realizations. helps assess various trade-offs among selected goals guides decision maker(s) effectively manage chain. applicability utility been demonstrated using case Saudi Arabia solved improved augmented ε -constraint algorithm. impact products obtained results investigated. Value Stochastic Solution (VSS) total cost, revenue, service level reached maximum 12.6%, 0.4%, 6.2% wait-and see solutions, respectively. proved importance over deterministic approach. addition, indicate that higher performance than price.