Bayesian optimization algorithm for multi-objective solutions: application to electric equipment configuration problems in a power plant

We apply Bayesian optimization algorithm with tabu search (tabu-BOA) to electric equipment configuration problems in a power plant. Tabu-BOA is a hybrid evolutionary computation algorithm with competent GAs and metaheuristics. The configuration problems we consider have complex combinatorial properties with multiple objectives, therefore, they are hard to solve via conventional techniques. First, we investigate the performance of the proposed algorithm using simple test functions, Next, using the method, we solve the following practical problems: both (1) minimize the cost of implementation and operation, and (2) maximize the marginal supply capacity in operation.