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Titlebook: Container Terminals and Automated Transport Systems; Logistics Control Is Hans-Otto Günther,Kap Hwan Kim Book 2005 Springer-Verlag Berlin H

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樓主: digestive-tract
31#
發(fā)表于 2025-3-26 22:20:11 | 只看該作者
32#
發(fā)表于 2025-3-27 04:28:59 | 只看該作者
https://doi.org/10.1007/978-3-662-32644-2 results of the simulation analysis, we determined the savings effect by cycle time and the required number of vehicles. We demonstrated that the ALV is superior to the AGV in both productivity and efficiency principally because the ALV eliminates the waiting time in the buffer zone.
33#
發(fā)表于 2025-3-27 06:08:13 | 只看該作者
https://doi.org/10.1007/978-3-662-32645-9 to total lateness of the AGVs. The main focus of the numerical investigation is on evaluating the priority rule based approach for single and dual-load vehicles as well as comparing its performance against the MILP modelling approach.
34#
發(fā)表于 2025-3-27 09:33:00 | 只看該作者
35#
發(fā)表于 2025-3-27 13:50:37 | 只看該作者
36#
發(fā)表于 2025-3-27 19:52:31 | 只看該作者
Dispatching multi-load AGVs in highly automated seaport container terminals to total lateness of the AGVs. The main focus of the numerical investigation is on evaluating the priority rule based approach for single and dual-load vehicles as well as comparing its performance against the MILP modelling approach.
37#
發(fā)表于 2025-3-27 23:23:18 | 只看該作者
Modeling and optimization of the intermodal terminal , em. In this approach, sequence-dependent duration of empty moves, alternative assignments (of containers to cranes) and a sequence-dependent number of operations have to be handled. An optimization model based on Constraint Satisfaction is formulated and heuristics for the search procedure, especially value and variable ordering are developed.
38#
發(fā)表于 2025-3-28 02:50:37 | 只看該作者
39#
發(fā)表于 2025-3-28 09:15:27 | 只看該作者
40#
發(fā)表于 2025-3-28 10:54:56 | 只看該作者
https://doi.org/10.1007/978-3-662-32645-9quently, we discuss priority rule based heuristics as well as a genetic algorithm for the general model. Based on a tailored generator for experimental data, we examine the performance of the heuristics in a computational study. We obtain promising results that suggest that the genetic algorithm is well suited for application in practice.
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