Equipment Disassembly and Maintenance in an Uncertain Environment Based on a Peafowl Optimization Algorithm

Disassembly sequence planning (DSP) is a key approach for optimizing various industrial equipment-maintenance processes. Finding fast and effective DSP solutions plays an important role in improving maintenance efficiency quality. However, when disassembling equipment, there are many uncertainties that can have detrimental impact on the disassembly subsequent work. Therefore, this paper proposes multi-objective problem uncertain environment addresses process through stochastic planning, with objectives of minimizing time enhancing responsiveness to priority components. Due complexity problem, improved peafowl optimization algorithm (IPOA) proposed efficient problem-solving. The specifically designed incorporates four customized mechanisms: peafowls’ courtship behavior, adaptive behavior female peafowls proximity, search chicks, interactive among male peafowls. These mechanisms enable optimal or near-optimal solutions. Through comparisons real-world case other advanced algorithms, superiority IPOA solving problems demonstrated. This research contributes quality, bringing positive impacts equipment maintenance.