This　article　proposes　a　novel　method,　named　the　cooperative　and　competitive　krill　herd　(CCKH)　algorithm,　in　which　both　cooperative　strategy　and　competitive　strategy　are　introduced　to　solve　the　structural　optimization.　In　the　cooperative　strategy,　a　crossover　operator　is　established　between　the　＇best　krill＇　and　＇food＇　to　generate　＇cooperative　krill＇,　which　facilitates　a　balance　between　global　exploration　and　local　exploitation.　In　the　competitive　strategy,　krill　individuals　with　poor　fitness　are　replaced　with　robust　＇competitive　krill＇　to　accelerate　global　convergence.　Then,　the　experimental　results　from　CEC2017　benchmark　functions　demonstrate　that,　compared　with　other　algorithms,　CCKH　shows　superiority　in　most　cases.　Finally,　six　structural　optimizations　are　used　to　evaluate　the　robustness　of　CCKH　compared　with　other　techniques.　It　is　found　that　as　the　complexity　of　the　structure　increases,　the　competitiveness　of　CCKH　becomes　more　pronounced,　and　the　time　complexity　of　the　presented　method　is　not　affected　by　the　two　strategies.