Improved model and application of multi-objective optimization problem

Daqi Dai

doi:10.1117/12.2688947

18 July 2023 Improved model and application of multi-objective optimization problem

Daqi Dai

Proceedings Volume 12744, Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023); 1274410 (2023) https://doi.org/10.1117/12.2688947
Event: Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 2023, Nanjing, China

Abstract

Multi-objective decision making with multiple constraints is a common and difficult problem in intelligent manufacturing and other fields. Through the simulation of management decision-making process, the demand objectives are classified according to attributes, and different target modules are constructed. According to the actual needs of enterprise production, each target module is sorted or combined. Based on the improved genetic algorithm, a Multi-Objective Decision-Making Combination Optimization Model (MODMCOM) with different levels or different structures is established. MODOM fully guarantees the running efficiency of the model and avoids the generation of bad solutions. The most important thing is that this solution model can avoid subjectivity when using traditional decision-making methods to select optimal schemes. By simulating the real process of management decision-making, the model provides a scientific basis for the final scheme selection with the support of intelligent algorithms. The feasibility and effectiveness of the model in solving the problem of multiple conditions and multiple objectives are verified by an example of flexible job shop scheduling decision-making in an enterprise, and the application value of the model in complex systems is illustrated.

Citation Download Citation

Daqi Dai "Improved model and application of multi-objective optimization problem", Proc. SPIE 12744, Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 1274410 (18 July 2023); https://doi.org/10.1117/12.2688947

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