Optimal Research on Production Decision Based on Profit Maximization and Violent Search Algorithm

In electronic product manufacturing, balancing quality control and cost control has become increasingly challenging due to complex assembly processes and multiple influencing factors. This study proposes a production decision-making optimization model based on profit maximization, considering various factors including parts inspection, finished product inspection, disassembly strategy, and exchange loss. Four 0-1 decision variables are introduced to describe the detection and dismantling strategy, with the objective function constructed by combining assembly parameters, detection costs, dismantling costs, and replacement losses. Through violent search algorithm optimization of 16 different inspection and dismantling strategies, the results show that optimal decisions vary significantly under different parameter scenarios. For instance, strategy "1101" achieves the highest profit of 15.966 in low defective rate scenarios, while strategy "0000" performs better with 18.587 profit in high defective rate scenarios. The study demonstrates that testing and dismantling strategies should be dynamically adjusted based on defective rates and costs, with optimal decisions increasing profit by 8%-12%.