Genetic algorithm-based counter-flooding decision model for damaged warship

Abstract

A good counter-flooding strategy is vital to the decision maker in case of emergency, but how to evaluate the scheme is still lack of a definite function. To establish a definite evaluation standard, this paper presents a counter-flooding decision model for scheme evaluation and decision support in shipboard flooding emergency. It adopts genetic algorithm to solve the proposed optimization model, which involves the combination of counter-flooding tanks that should be filled or evacuation in order to achieve an optimal response to a flooding accident. The genetic algorithm is developed with roulette wheel selection, one-point crossover, mutation, and iterative process continues until terminating condition is encountered. The stopping criterion proposed in this paper is the tilt angle, also the heeling angle is another terminate rule. The computational results validate the effectiveness of proposed optimization model and genetic algorithm.