In addition to optimal performance and efficiency, several other practical criteria can be integrated into multi-objective heuristic design. One such criterion is robustness, which measures a heuristic's performance consistency across various problem instances and conditions. This is particularly important in real-world applications where problem characteristics may vary significantly. Another criterion is scalability, which assesses how well a heuristic performs as the problem size increases. This is crucial for ensuring that heuristics remain effective in larger, more complex scenarios. Maintainability and readability of the code are also vital, as they influence the ease with which heuristics can be modified or extended by practitioners. Finally, resource consumption, including memory usage and computational overhead, should be considered to ensure that heuristics are not only effective but also practical for deployment in resource-constrained environments.