An Integrated Mathematical Model of Production Planning Considering Order Acceptance, Production and Customer Delivery at Marun Petrochemical Company

The scheduling and batch delivery problem has been studied by many researchers as one of the classic operation sequence problems. However, this study attempted to address this problem by adding order acceptance determination and sequence-dependent setup. In this study, a mathematical model has been presented in Marun Petrochemical Company considering the number of orders received for production to maximize the organization's profit by selecting the order and planning the production based on the order received. Therefore, to realize this goal in the small production space, the mathematical model was coded in GAMS software and solved using the CPLEX solving method. Then, to investigate the larger scale of the model under study, the validation of 23 generated problems was carried out by the exact solution in GAMS software and genetic algorithm in MATLAB software, and in the end, the comparative evaluation was performed. The evaluation showed that the meta-heuristic solution on a small scale has a small deviation from the exact solution, and the mathematical model is solved in a proper time by the meta-heuristic algorithm. As the problem's size grows up, the exact solution loses its efficiency in terms of time, and the application of the exact solution algorithm to solve the model becomes inadequate. The genetic algorithm achieves an acceptable solution in a proper time with reasonable deviation. So, this algorithm can replace the exact solution properly.