Solving fuzzy dynamic ship routing and scheduling problem through new genetic algorithm
Madhushree Das, Arindam Roy, Samir Maity, Samarjit Kar, Shatadru Sengupta
Abstract
This paper develops a model for shipping of container vessels to fulfill the demand and supply in various ports in a fixed time frame with dynamic demand and supply of each port under fuzzy environment. The time frame is divided into sub-frames which are operation time and travelling time. Speed optimization, simultaneous loading, unloading operation, and load factor are introduced to reduce fuel consumption and carbon emission. The risk factor is introduced to make the problem more realistic. In the real ship routing scenarios, different cost parameters are not always deterministic, and fluctuate imprecisely. The imprecise cost parameters are considered as Triangular Fuzzy Number (TFN). A modified genetic algorithm is used to solve the proposed model, and numerical examples are given to illustrate the efficiency of the proposed algorithm.