Site selection for tank cleaning station based on genetic algorithm with multiple discrete variables

The concept of "cabin washing heat value（CWHV）" for ports is introduced to reflect the eagerness of a port for cabin washing, and the cabin washing heat values of interested ports are determined. The location selection model for cabin washing station is built with the objective function for lowest overall cost. The location and the scale of the cabin washing station are taken as the decision variables. A modified dual chromosome genetic algorithm is used to solve the model. The modification includes CWHV-based initial selection strategy, adaptive crossover probability and elite retention strategy. The planning of cabin washing stations for a group of ports on the Yangtse River is carried out as an example. The solution was 6 cabin washing stations distributed at ports with higher CWHV, which guarantees minimum deadhead kilometers, about 250km/（ship·year）. The process demonstrated the efficiency advantage of genetic algorithm over Lingo solver for large scale problems.