Evolutionary　computation　based　on　the　idea　of　biologic　evolution　is　one　type　of　global　optimization　algorithm　that　uses　self-adaptation,　self-organization　and　random　searching　to　solve　optimization　problems.　The　evolutionary-simplex　algorithm　is　introduced　in　this　paper.　It　contains　floating　encoding　which　combines　the　evolutionary　computation　and　the　simplex　algorithm　to　overcome　the　problems　encountered　in　the　genetic　algorithm　and　evolutionary　strategy　methods.　Numerical　experiments　are　performed　using　seven　typical　functions　to　verify　the　algorithm.　An　inverse　analysis　method　to　identify　structural　physical　parameters　based　on　incomplete　dynamic　responses　obtained　from　the　analysis　in　the　time　domain　is　presented　by　using　the　evolutionary-simplex　algorithm.　The　modal　evolutionary-simplex　algorithm　converted　from　the　time　domain　to　the　modal　domain　is　proposed　to　improve　the　inverse　efficiency.　Numerical　calculations　for　a　50-DOF　system　show　that　when　compared　with　other　methods,　the　evolutionary-simplex　algorithm　offers　advantages　of　high　precision,　efficient　searching　ability,　strong　ability　to　resist　noise,　independence　of　initial　value,　and　good　adaptation　to　incomplete　information　conditions.