Abstract：Continuous-time models need more computational effort to solve refinery production scheduling problems as the scheduling problem size increases. A new Lagrangian decomposition approach was used which divides the whole scheduling problem into nine subproblems. The convergence of Lagrange multipliers is accelerated by adding auxiliary constraints to the subproblems. This paper gives an initialization scheme for the Lagrange multipliers, a hybrid method to update the Lagrange multipliers and a heuristic algorithm to find feasible solutions. Computational results for three cases with different time horizons and different numbers of orders show that the Lagrangian scheme improves the computational efficiency and obtains optimal or near-optimal solutions.
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