Decomposition of integrated scheduling and dynamic optimization problems using community detection

In this paper the decomposition of the integrated cyclic scheduling and dynamic optimization problem is analyzed using community detection. Different production systems are examined and based on the results of the community detection and the centrality of the constraint unipartite graph, a two level hierarchical structure is identified, with the scheduling problem in the first level and the dynamic optimization subproblems in the second level. The variables that link the two levels are continuous and obtained from the results of the community detection. Finally, Generalized Benders Decomposition is applied on the decomposed optimization problem obtained from the community detection and a solution is obtained faster than solving the problem monolithically.