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Artificial immune network has been receiving particular attention over the last few years. Recent researches have revealed that, without stimulation and cooperation of network cells, lots of redundant explorations waste ldquoresourcesrdquo, which affects searching ability and searching speed. In this paper, a cooperative artificial immune network denoted CoAIN is devised for multimodal function optimization. To explore and exploit searching space efficiently and effectively, the interactions within the network are not only suppression but also cooperation. Network cells cooperate with particle swarm behavior making use of the best position encountered by itself and its neighbor. Numeric benchmark functions were used to assess the performance of CoAIN compared with opt-aiNet, BCA, hybrid GA, and PSO algorithms.