Positioning empty containers under dependent demand process
Owing to trade imbalance, shipping companies position empty containers between ports or depots periodically. The most difficult problem for positioning is that it is not possible to know the exact amounts of empty containers required in the future. The paper deals with the problem of positioning empty containers in a port area with multiple depots. Customer demands and returning containers in depots per unit time period are assumed to be serially-correlated and dependent random variables. Three options are considered to prepare the required extent of positioning: positioning from other overseas ports, inland positioning between depots, and leasing. The policies for empty-container management consist of three parts as follows: a coordinated, (s, S) inventory policy for positioning from other ports, (r(i), R-i) policy for inland positioning between depots; and a simple leasing policy with zero lead-time. For inland positioning policy, four heuristic methods are proposed to reposition empty containers between depots. The objective is to obtain optimal policies corresponding to different methods of inland positioning in order to minimize the expected total costs. A genetic-based optimization procedure is developed to find the optimal parameters (s, S) and (r(i), R-i). Some numerical examples and sensitivity analyses are given to demonstrate the results. (c) 2011 Elsevier Ltd. All rights reserved.
empty containers inventory policies genetic algorithm