A novel multi-agent evolutionary algorithm for assembly sequence planning

作者：Zeng Congwen; Gu Tianlong; Chang Liang; Li Fengyin

来源：Journal of Software, 2013, 8(6): 1518-1525.

DOI：10.4304/jsw.8.6.1518-1525

• Approximate solution
• Assembly process information
• Assembly sequence planning
• Evolutionary process
• Learning
• Mutation

Many evolutionary algorithms for assembly sequence planning (ASP) have been researched. But those algorithms have lots of blind searching because individuals have little consideration about geometry and assembly process information of product in the evolutionary process. To improve individuals' intelligence and decrease blind searching, motivated by the self-assembly computing and multi-agent evolutionary algorithm, a novel multi-agent evolutionary algorithm for assembly sequence planning (NMAEA-ASP) is presented. In the algorithm, learning, competition and mutation are designed for each agent. Learning, competition and mutation are realized by assembly and disassembly. Some notions such as assemblyunit, power about assembly are also introduced. Experimental results show that NMAEA-ASP can find an approximate solution faster than other evolutionary algorithms.

• 出版日期2013
• 单位西安电子科技大学