The　design　of　an　effective　antenna　array　is　a　major　challenge　encountered　in　most　communication　systems.　A　much-needed　requirement　is　obtaining　a　directional　and　high-gain　radiation　pattern.　This　study　deals　with　the　design　of　a　linear　antenna　array　that　radiates　with　reduced　peak-side　lobe　levels　(PSLL),　decreases　side-lobe　average　power　with　and　without　the　first　null　beamwidth　(FNBW)　constraint,　places　deep　nulls　in　the　desired　direction,　and　minimizes　the　close-in-side　lobe　levels　(CSLL).　The　nature-inspired　metaheuristic　algorithm　multi-verse　optimization　(MVO)　is　explored　with　other　state-of-the-art　algorithms　to　optimize　the　parameters　of　the　antenna　array.　MVO　is　a　global　search　method　that　is　less　prone　to　being　stuck　in　the　local　optimal　solution,　providing　a　better　alternative　for　beam-pattern　synthesis.　Eleven　design　examples　have　been　demonstrated,　which　optimizes　the　amplitude　and　position　of　antenna　array　elements.　The　simulation　results　illustrate　that　MVO　outperforms　other　algorithms　in　all　the　design　examples　and　greatly　enhances　the　radiation　characteristics,　thus　promoting　industrial　innovation　in　antenna　array　design.　In　addition,　the　MVO　algorithm＇s　performance　was　validated　using　the　Wilcoxon　non-parametric　test.