Implement Multi-Objective Bayesian Optimization

Using BoTorch and the Multi-objective Bayesian Optimization (MCP) framework, implement an optimization loop to discover the optimal design parameters for your memristor array. Your objectives should include maximizing the accuracy of the Bayesian inference task and minimizing the simulated energy consumption per inference. Define a clear search space for your memristor model parameters and specify the acquisition function and surrogate model used in BoTorch. The optimization process should iteratively call your `MemristorArraySimulator` for evaluation.