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The importance of Wireless Sensor Networks (WSNs) has increased owing to their extensive advances, allowing integration of nano-sensors, wireless networks, and smart software. The main challenge in WSNs is the fast sensor energy discharging. One of the most effective approaches to deal with this issue is clustering and selecting appropriate cluster heads. This study presents a Fuzzy Shuffled Frog Leaping Algorithm (FSFLA), which employs the memetic Shuffled Frog Leaping Algorithm (SFLA) to optimize the Mamdani fuzzy rule-base table based on the application specifications. In addition to automatically adjusting the if-then fuzzy rules, this protocol optimizes five controllable parameters associated with the inputs to the fuzzy system in an offline procedure prior to launching the network. The inputs of the fuzzy systems include remaining energy, distance from the base station, the number of neighboring …