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A novel weight coefficient cluster covering genetic algorithm for multi-objective optimization and its implementation based on Delphi 7.0 are discussed. First, the principle and key technologies of the algorithm are presented, including cluster covering, accurate decoding and fuzzy decoding, etc. Then, its workflow is analyzed. Its main modules include input module, computing module, output module, and operational module. Its operational process is illustrated. The influence of algorithm parameters on computing results is also analyzed. The results show that the algorithm is validated. The algorithm can adopt several computing patterns. Both accurate decoding and fuzzy decoding have good astringency and diversity distribution. It is easy to use and its visualized result analyzing sub-system can output both data and graphs. The alternative employment of accurate decoding and fuzzy decoding can further improve its performance. These instructions give you basic guidelines for preparing papers for conference proceedings.