To　resolve　the　conflicts　among　the　objectives　in　the　multi-objective　optimization,　the　information　among　the　objective　values　should　be　objectively　mined　by　using　similarity　theory.　A　new　multi-objective　optimization　method　based　on　discrete　Fréchet　distance　was　presented.　The　binary　mapping　combination　of　Z-score　standardization-Max-value　normalization　was　established,　by　which　Pareto　front　and　corresponding　objective　function　values　of　ideal　solution　were　mapped　into　discrete　and　ordered　point　chains,　then　the　multiple　comparison　curves　and　a　reference　curve　were　built.　The　discrete　Fréchet　distance　was　utilized　to　measure　the　similar　degree　between　the　reference　curve　and　the　comparison　curves　to　achieve　the　multi-objective　optimization,　and　was　also　deemed　as　the　fitness　of　GA　algorithm　to　guide　the　algorithm　evolution.　Compared　with　the　experiments　of　the　other　three　algorithms,　the　optimization　solution　and　various　performance　indicators　obtained　by　the　new　algorithm　were　mostly　superior,　which　proved　the　feasibility　and　effectiveness　of　the　new　algorithm.　©　2017,　Editorial　Department　of　CIMS.　All　right　reserved.