<p>Improving the reliability of coherent systems in process-oriented industries is essential for minimizing yield losses. A major challenge arises from the use of heterogeneous components within the system structure, which makes reliability calculations more complex and time-consuming. This paper investigates a reliability–redundancy allocation problem (RRAP) involving heterogeneous standby components. In subsystems with heterogeneous standby components, the activation sequence plays a crucial role in enhancing reliability; thus, determining the optimal sequence becomes the primary objective of the optimization problem. To address the challenge of managing a wide range of component reliability options, a Markov-based method is employed. Unlike existing approaches, the developed Markov model not only calculates the exact system reliability but is also sensitive to the defined activation order of components. Consequently, the optimal activation order can be identified by comparing the overall reliability of all possible activation sequences in negligible time. To evaluate the effectiveness of the proposed model, three well-known benchmarks were applied. Since such problems belong to the NP-hard class of optimization problems, a powerful hybrid metaheuristic algorithm, SFS-GA, was employed. Due to the intensive computations involved in solving NP-hard optimization problems, high-performance computing resources are used to achieve timely and accurate solutions. Numerical results demonstrate that the use of heterogeneous components provides a significant advantage over traditional RRAP models. Moreover, the results indicate that arranging components in descending order has a substantial impact on improving overall system reliability.</p>