In recent years, many accidents have occurred in the chemical industries, and these have concerned their complex and high-risk processes. Generally, these incidents expose industry and society to many kinds of adverse consequences, which can impact multiple dimensions of consequence. Thus, one way to prevent and/or mitigate these risks is to implement effective risk management practices. In the risk management process, one of the major challenges faced by decision-makers is to ascertain which set of actions should be undertaken to reduce or mitigate critical risks, given that the resources available for such actions are scarce and limited. Therefore, this paper proposes a decision support model to optimize plans for responding to multidimensional risk in industry. The decision problem consists of determining which preventive and/or mitigating actions should be implemented to maximize reducing multidimensional risk, according to the hierarchy of risk priorities and the constraints on available resources, while also taking the decision-maker's preference structure into account. also considering the preference structure of the decision maker. A numerical application was used, in a hypothetical plant that produces methanol, to evaluate the proposed model. The results obtained proved the applicability and efficiency of the model at optimizing the plans for responding to risk and took full account of the risk priorities that had been established.