Abstract :
The paper focuses on determining the storage position of the reshuffled container during dynamic retrieving outbound container for loading ship. The study concentrates on a yard bay with several tiers in every stack. For minimizing the uncertainty influence of relocation on the loading ship system and ensuring the fluency of loading operations, we suggest besides minimizing the total number of reshuffles, controlling the number of reshuffles for single retrieve container operation into average is also very necessary. The optimization model is built, with an objective to minimize the total number of reshuffles for the operations, and with constraints to ensure the number of reshuffles for each retrieve container operation within the average range furthest. Considering the influence of reshuffled container´s relocation on the retrieving container and the containers to be retrieved later, the abstract constraints are transformed into several rules for confirming the feasible storage positions of reshuffled container. These rules are exact substitute for the constraints, which do not induce additional restriction or relax the constraints of the original problem. With the optimization plan not losing, it avoids infeasible relocation plan forming entirely. Importantly, it is very simple and needn´t complex parameter computation. The forming flow of the relocation plans based on these rules is achieved and the optimization plan with the minimum total number of reshuffles can be got from them. The optimization model and methods proposed are also fit for other yard bay in container terminal. Additionally, they can be used in relocating other types of products during retrieve operations such as boxes, pallets, et al. with the similar stacking and relocation mode to the outbound containers´.
Keywords :
bulk storage containers; freight handling; loading; ships; boxes; container terminal; container yards; intrabay relocation plan; loading operations; loading ship; outbound container; pallets; reshuffled container; storage; yard bay; Constraint optimization; Containers; Control systems; Logistics; Marine vehicles; Mechanical engineering; Optimization methods; Paper technology; Storage automation; Uncertainty; Optimization; container terminal; container yard; marshalling; relocation;