Simulate Emotion Space Model Of The Artificial Plant Algorithm

Artificial plant optimization algorithm (APOA) is a new population-based evolutionarycomputation inspired by plant growing process. It mimics the photosynthesis, phototropismand apical dominance mechanisms. APOA achieves good performance when solvinghigh-dimensional multi-modal problems because plant is more adaptive than animals. In thispaper, a new variant of phototropism operator is designed, and the values of additionalparameters are chosen by uniform design. To test the performance, this new variant is appliedto reactive power optimization and optimal coverage configuration of wireless sensornetworks.(1) The standard version of APOA only considers the influence of sunlight, while otherfactors are omitted, such as water and trace elements. Generally, the growing speed of plant iscontrolled significantly by water. Therefore, in this paper, the influence of water is introduced,and a new variant of phototropism operator is designed including one2-D sunlight-watermodel which is inspired by OCC model. This new algorithm is called APOA with emotionalspace. To test the performance, it is applied to several famous benchmarks, numerical resultsshow this new operator improves the performance significantly especially forhigh-dimensional multi-modal problems.(2) In this new variant of phototropism operator, nine paramters are added, and theirvalues influence the performance significantly, therefore, uniform design and PLSR (partialleast squares regression) are employed to discuss the values.(3) Reactive power optimization is an important measure by improving the voltageprofile and reducing the active loss. It is a multi-variable, multi-constraint nonlinearprogramming problem. In this paper, one mathematical model by minimizing active loss andvoltage deviation is employed, and artificial plant optimization algorithm with emotionalspace is applied to solve it with IEEE57bus power system and IEEE118bus power system.Simulation results show it is feasible.(4) The optimal coverage problem plays an important role in wireless sensor networks.In this paper, APOA with emotional space is applied to solve it. Simulation results show it iseffective.