Year: 2026
Type: article
Abstract: With the rapid development of digital technologies and automation of production processes, food industry enterprises are increasingly focusing on improving production management efficiency. Improving production planning is a key area, as the efficient use of resources, timely order fulfillment, cost reduction, and increased competitiveness depend on the quality of production schedules. This task is particularly challenging for bakeries, where the production cycle includes numerous interrelated operations, the execution of which requires strict adherence to time and resource constraints. Bakery production is a multi-stage process, including raw material preparation, dough preparation, product molding, proofing, baking, cooling, and packaging of finished products. Each of these operations is performed on specific equipment and has its own technological requirements. Furthermore, various production orders can simultaneously compete for the enterprise's limited resources, significantly complicating the planning process. In such circumstances, traditional scheduling methods often prove ineffective, especially as production volumes and the number of orders increase. This study examines the application of the CP-SAT (Constraint Programming Satisfiability) method to solving the problem of optimal production process planning at a bakery. This method is a modern combinatorial optimization tool and enables efficient solutions to problems containing a large number of interrelated constraints. CP-SAT allows for the consideration of process characteristics, equipment constraints, operational sequence requirements, and time dependencies between individual production stages. To solve this problem, a mathematical production planning model was developed that reflects the structure of a bakery's production process. The model takes into account production operations, available resources, job durations, and equipment operating conditions. Additionally, the possibility of parallel execution of individual processes is considered, allowing for more efficient utilization of available production capacity. The objective function of the model is to minimize the overall production plan execution time, thereby reducing product manufacturing time and improving plant efficiency. The practical implementation of the proposed approach was accomplished using the Google OR-Tools library, which contains a high-performance CP-SAT solver. Based on the developed model, an algorithm for automated production scheduling was created. Experiments demonstrated the method's ability to effectively account for numerous process constraints and generate high-quality production plans within a reasonable computation time. The results confirm the potential of constraint programming methods for solving production planning problems in the bakery industry. Thus, the use of CP-SAT technology improves the quality of production process planning, ensures more efficient equipment utilization, and reduces order fulfillment time. The proposed approach can serve as the basis for developing intelligent decision support systems aimed at automating production management and increasing the efficiency of food industry enterprises.
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7224492785