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Comparing allocation and relocation policies at a logistics service container terminal: a discrete-event simulation approach


This research is focused on the analysis of a container terminal common in industrial zones in urban areas, called the logistic services container terminal (LSCT), defined as a small to medium size inland terminal with no intermodal facilities. The main function of an LSCT is to provide services to a hinterland market. The material handling equipment used is limited to reach stacker cranes and front loaders, and ground transportation in and out is performed using trucks exclusively. Moreover, there are many operations related to servicing customers in special service areas within the yard. In this research, we explicitly recognize the limitations and features associated with the operations within LSCT yards, which means that the problems and solutions must be conceived and addressed in a very unique way, considering that services have to be coordinated with the strategies proposed for managing the movement of containers in and out. This paper characterizes the different aspects present in the treatment of an LSCT and proposes an adapted version of three known greedy decision rules for determining the location for an arriving container. We evaluate the performances of these rules using a discrete-event simulator: the min-max rule outperforms the other tested rules. These rules are also extended to consider the cost of moving relocating containers. The results show that using cost-aware rules while increasing the expected number of relocations reduces the total expected cost significantly.

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The authors want to acknowledge the support of project ANID/FONDECYT/REGULAR 1191200 and the Complex Engineering Systems Institute ANID PIA/PUENTE AFB220003. Juan Pablo Cavada is grateful for the support of ANID BECA DOCTORADO NACIONAL 21171505.

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Correspondence to Juan P. Cavada.

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A: Alternative layout analysis

A: Alternative layout analysis

The yard layout used in the presented case study corresponds to the configuration found in our modeled case study for LSCT. However, to make some sensitivity, to check if the results, analysis and conclusions hold true when using certain options of alternative layout, we tested two more configurations of a potential LSCT yard. The variants in configuration are the line abreast layout, were containers blocks are positioned side by side from the widest side, and the column layout where blocks are located one after the other. See Fig. 16

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figure 16

Alternate yard layouts tested

We chose to test the three “staggered” rules: MM-S, RIL-S and RI-S in each configuration. One hundred replications where run for each layout-rule combination, and later a paired t-test was conducted for each combination. The results are summarized in Tables 4 and 5.

Table 4 Simulation results for each alternate layout
Table 5 Rule comparison for each alternate layout

In concordance with the results for the base case presented in Sect. 7, the results of these alternative configurations show that the MM-S rule outperforms the other two in all the layouts tested in this work.

Although the average cost for the MM-S is lower than the average cost for the RIL-S in the three layouts tested, the differences are small, and not significant at 95% of significance according to a t-test for the hypothesis that the average costs for the two rules are different.

In all cases using the line abreast layout yields the lowest cost, followed by the square and finally the column layout. This is an expected result, due to the fact that when to blocks are closer on the wide side, the cost of moving blocks between them is lower.

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Cavada, J.P., Cortés, C.E. & Rey, P.A. Comparing allocation and relocation policies at a logistics service container terminal: a discrete-event simulation approach. Cent Eur J Oper Res 31, 1281–1316 (2023).

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