Artificial　bee　colony　(ABC)　algorithm　is　a　novel　search　algorithm　which　simulates　the　intelligent　foraging　behavior　of　honeybee　swarm　to　solve　the　practical　problems.　However,　there　is　only　a　behavior　communication　way　(dancing)　in　the　current　ABC　algorithm,　which　results　in　the　lack　and　lag　of　collaboration　among　bees　and　influences　the　solving　performance　of　ABC　algorithm.　Inspired　by　the　objective　fact　of　transinformation　among　real　bees,　a　new　ABC　algorithm　is　proposed　by　introducing　a　chemical　communication　way　based　on　inductive　pheromone　and　applied　to　solve　multidimensional　knapsack　problems　(MKP),　which　is　more　faithful　to　the　transmission　information　of　real　bee　colony　system.　With　the　combination　of　the　behavior　communication　way　and　the　chemical　communication　way,　the　new　algorithm　makes　the　honeybees　cooperate　with　each　other　better　by　the　scheme　of　inductive　pheromone　updating　and　diffusion.　A　number　of　simulation　experiments　and　comparisons　on　benchmark　datasets　of　MKP　demonstrate　that　the　performance　of　the　new　algorithm　is　superior　over　the　original　ABC　algorithm.　The　performances　of　the　new　algorithm　have　also　been　compared　with　some　typical　meta-heuristic　search　algorithms,　and　the　computational　results　show　that　the　new　ABC　algorithm　obtains　better　quality　solutions　than　all　the　other　approaches.