Modeling and optimization of ocean-going unloading problem with stochastic demand

One of the important Challenges for steel enterprises is to reduce the procuremen 1 t cost occurred in unloading process of ocean-going ship, ore as the main material contains usually some uncertain demand, and its unloading process is a typically complex problem with large scale. In this paper, unloading cost composition is analyzed strictly, and its mathematical model with stochastic demand is established wherein various complex constrains are considered. Further, Lagrangian relaxation algorithm and genetic algorithm combined with sub-gradient is designed to solve this problem. Finally, an example is simulated and illustrated to interpret the effectiveness and accuracy of proposed algorithm.