الگوریتم هیوریستیک برای برنامه ریزی محوطه کامیون و مشکلات تخصیص ذخیره سازی

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.

Container terminals perform as joints of land and marine transportation, and they serve as hubs and transfer stations of multimodal transportation. Shipping industry accounts for more than 75% market share in modern logistics. The efficiency of the stacking and the transportation of large number of containers to and from the quayside is critical to any container terminal (Stahlbock and Voß, 2008). Typically, there are three types of container handling systems engaged in container terminals: chassis, straddle-carrier and transtainer systems, the latter being the most popular in major terminals due to the need for high container storage capacity in the yard. For the transtainer system, there are three types of handling equipments employed, namely quay cranes, yard cranes and yard trucks. Quay crane is usually the most expensive handling equipment, and also potentially the bottleneck in the loading and discharging operations in container terminals. After discharged from container vessels, containers will be allocated to yard blocks for temporary storage. In yard, yard cranes are engaged for picking and stacking containers from and to yard blocks. Yard trucks move containers between quayside and yard side, so as to satisfy the schedules of quay crane and yard crane. Due to the limitations of modeling and computation, the complete container terminal operations are rather unlikely to be analytically formulated and efficiently solved (Steenken et al., 2004). A practical way of improving the efficiency of container terminal operations is to identify and resolve a series of optimization problems. In general, these optimization problems include berth allocation problem, quay crane scheduling problem, yard truck scheduling problem, yard crane scheduling problem and storage allocation problem. This paper focuses on the yard truck scheduling and storage allocation problems. Followed by this introductory section and a literature review in Section 2, it also describes the integrated yard truck scheduling and storage allocation problems. A mixed integer programming (MIP) model is formulated for the proposed problem in Section 3. In Section 4, a heuristic solution algorithm is developed for effective problem solutions. A series of computational experiments are illustrated in Section 5 to test some key factors of the problem and the performance of the solution algorithm. Finally, Section 6 concludes this paper.

To conclude, the contributions of this paper to literature are: 1. It provides a novel idea for improving the efficiency of container terminal operations by integrating yard truck scheduling and storage allocation into a whole. Unlike previous studies (Bish et al., 2001, Bish, 2003 and Lee et al., 2008), both loading and discharging requests are considered, so that the empty moves of yard trucks can be reduced. The proposed problem is formulated as a mixed integer programming model, the objective function minimizes the weighted summation of total travel time of yard trucks and total delay of loading and discharging requests. 2. A constructive heuristic, HIA, is developed to solve the proposed problem. The HIA integrates the insertion heuristics and auction algorithms and has demonstrated its efficiency in problem solving. In HIA weight parameters can be chosen to reflect the requirements of decision maker, as illustrated in computational experiments. Yard truck scheduling and storage allocation problems are well-known intractable problems in container terminal operation. The importance of integrating these two problems has been pointed out by Bish et al. (2001). There exist few methods that can solve large scale yard truck scheduling and storage allocation problem. Though HIA achieves near optimal solutions to the yard truck scheduling and storage allocation problem, it can solve the practical size problem online for both loading and unloading operations. The approach proposed in this paper provides a novel idea to handle the problem as well as other optimization problems in container terminal operations. In future research, the development of better solution algorithms will still be an emphasis on the study of integrated optimization model in container terminal operations.