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Why Simheuristics? Benefits, Limitations, and Best Practices When Combining Metaheuristics with Simulation
2017
Social Science Research Network
From smart cities to factories and business, many decision-making processes in our society involve NP-hard optimization problems. In a real environment, these problems are frequently large-scale, which limits the potential of exact optimization methods and justifies the use of metaheuristic algorithms in their resolution. Real-world problems are also distinguished by high levels of dynamism and uncertainty, which affect the formulation of the optimization model, its input data, and constraints.
doi:10.2139/ssrn.2919208
fatcat:ttanu6lsqfd7piqdzkgjp77nhm