| Summary: | 碩士 === 國立勤益科技大學 === 工業工程與管理系 === 107 === Disassembly Sequence Planning (DSP) refers to the disassembly sequence according to the disassembly property and restrictions of the product parts that meet the benefit goal. This study aims to reduce the number of change in disassembly direction and disassembly tools so as to reduce the disassembly time. This study proposes a novel Turbellaria algorithm that evolves through the regenerative properties of the Turbellaria. It is similar to the evolutionary concept of genetic algorithms, with evolution as the main idea, but without crossover, mutation and replication mechanisms in the evolutionary processes. Instead, it is based upon the characteristics of Turbellaria in growth, fracture and regeneration mechanisms. The Turbellaria algorithm features a variety of disassembly combinations and excellent mechanism to jump off the local optimal solution. Particularly, it has the advantage to keep the good disassembly combination from being destroyed. In this study, it is compared with two genetic algorithms and an ant colony algorithm and tested in three examples of different complexity: ceiling fan, printer, and simulated 150 parts. The solution searching ability and execution time were compared upon the same evaluation standard. The test results demonstrated that the novel Turbellaria algorithm proposed in this study is better than the other two genetic algorithms in the improvement of solution quality.
|
|---|
