The oviposition decision of the female bean weevil is assumed to minimize the effects of larval competition and to maximize her lifetime fitness. A dynamic, stochastic model is proposed for bean weevil oviposition behavior analysis in terms of fitness maximization. The behavioral processes of the optimal females with varied levels of larval competition and females using other strategies (one absolute and two relative rules selected here) were simulated with the Monte Carlo simulation. The accepting probability of beans with varied egg loads, and the cumulative number of eggs laid by females using distinct strategies were compared. Lifetime fitness was used to analyse the effect of natural selection on the oviposition behavior of bean weevil. The real rule used by the bean weevil can be explored by comparing experimental data with this information.
Dynamic programming, Simulation
