Abstract
This paper presents a new immune inspired algorithm, the Clonal Selection Algorithm for Multi-agent Itinerary Planning (CSA-MIP), to solve the MIP problem in wireless sensor networks. CSA-MIP has two computational stages called Stage I and Stage II. When only Stage I is activated in CSA-MIP, in the obtained solutions, the difference between the maximum and minimum numbers of sensor nodes, visited by each mobile agent, is relatively large. When only Stage II is activated in CSA-MIP, in the obtained solutions, the number of mobile agents is relatively small. When both stages are activated in CSA-MIP, in the obtained solutions, the diversity in the number of mobile agents can be achieved and the unbalance in the number of sensor nodes visited by each mobile agent can be reduced, which indicate a higher possibility to obtain solutions of better quality. Moreover, according to the simulation results and analysis of computational complexity, CSA-MIP is shown to perform better than GA-MIP in terms of solution quality and computational efficiency.
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