Multi-Objective Production Cost Control and Strategy Optimization Using Whale Optimization Algorithm

As competition in the global electronics manufacturing industry intensifies and market demands evolve, enterprises face the urgent challenge of minimizing production costs while ensuring product quality, and enhancing their competitiveness. This paper focuses on the issue of defective rates in spare parts 1, spare parts 2, and finished products during the electronics production process. It constructs a comprehensive optimization model for production testing and disassembling. The objective is to help enterprises maximize profits and reduce production costs by optimizing testing and disassembling strategies for spare parts and finished products and managing unqualified products effectively through disassembling or discarding. In this paper, we propose the following hypotheses: the probability of spare part i being tested is denoted as , the probability of a finished product being tested is denoted as P, and the disassembly rate of unqualified products is denoted as . Utilizing the Whale Optimization Algorithm (WOA), this paper establishes a multi-objective optimization model to seek the optimal strategy in the production process. Our findings indicate that, in scenario 4, testing spare parts and finished products but not disassembling unqualified finished products yields the optimal solution. The total expected cost under this strategy is approximately 29.99 yuan.