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Abstract. To solve the current situation of immature use of Baldwin effect in exsiting memetic differential evolution (DE), we propose a memetic differential evolution with Baldwin effect and opposite-based learning (mDEBO), in which, Hooke-Jeeves and DE are combined into memetic DE algorithm through Baldwin effect. The individuals with better local search tend to be learned by others, which makes the population more diverse. In addition, the opposition-based learning mechanism is used to speed up the convergence rate. Compared with other well-known differential evolution algorithms in 15 benchmark functions in CEC2015, mDEBO performs satisfied convergence ability.

According to the main characteristic of the city's water affairs dispatchment, the structure of water affairs dispatchment based on rough sets theory was proposed. After each factors were considered synthetically, knowledge expression system was set up, and the water affairs dispatchment control regulation was reduced and acquired. To some extent, it's a new method of processing the uncertain information in the water affairs dispatchment. The example demonstrates that this method has reduced the dispatchment control, and its regulation acquired is of objectivity, so it can solve preferably the control problem of the city's water affairs dispatchment.

Abstract. An intuitionistic fuzzy hybrid discrete particle swarm optimization (IF-HDPSO) is proposed for solving travelling salesman problem (TSP). By defining intuitionistic fuzzy charisma function, the IF-HDPSO algorithm exploits some other individuals to participate in the updates of velocity and position except the best one. In addition, the PSO identical factor function is defined to adjust inertia weight and learning operator adaptively, so the IF-HDPSO can explore the whole optimal solution quickly. Furthermore, an adaptive genetic algorithm based on elitist reserving strategy is developed, and combine it with PSO to reduce the probability of being trapped in the local optima and premature convergence. The simulation results indicate IF-HDPSO perform better on precision, iteration number and computational robustness.