a new model for balancing between asset sharing risk and responsiveness: developing the augmented ɛ-constraint method

In recent years, responsiveness in the supply chain network (scn) has been considered to improve competitiveness because customers are the most significant part of a supply chain, and promptly meeting customer demand is substantial. in this article, to deal with the technological risks, the reinforcement policy (rp) before the disruption and the assets-sharing (as) policy before and after the disruption has been used as resilience policies for disruption (rpd). also, the responsiveness of the network, as well as the risks associated with as, have been considered in mathematical modeling. in addition, lateral sending (ls), delivery time deviations, and penalties for lost sales for increasing customer satisfaction in the cost objective function are considered responsiveness policies. a solution method has been developed based on the augmented ɛ-constraint to solve the model. finally, the results show an improvement in cost by up to 14% and responsiveness by up to 17% by using the proposed policies, as well as the effectiveness of the developed technique to cope with the multi-objective (mo) model.