As process plants become more complex, the notion of reliability per se is insufficient to measure stable and cost-effective operations. Recently, the idea of resilience has been put forward as a means to quantify the amount of systemic failures a process plant can handle before its operations become significantly affected. This work proposes a framework for resilience-centered plant design. By this consideration, a triple-objective optimization problem (cost-reliability-resilience) was modeled. The problem was then solved using three metaheuristic strategies via the weighted-sum approach. The computational results reflecting the effectiveness of the proposed framework are discussed in detail. © 2017 Taylor & Francis.