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- Abourraja, Mohamed Nezar, et al.
(författare)
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A multi-agent based simulation model for rail–rail transshipment : An engineering approach for gantry crane scheduling
- 2017
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Ingår i: IEEE Access. - : IEEE Press. - 2169-3536. ; 5, s. 13142-13156
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Tidskriftsartikel (refereegranskat)abstract
- Le Havre Port Authority is putting into service a multimodal hub terminal with massified hinterland links (trains and barges) in order to restrict the intensive use of roads, to achieve a more attractive massification share of hinterland transportation and to provide a river connection to its maritime terminals that do not currently have one. This paper focuses on the rail-rail transshipment yard of this new terminal. In the current organizational policy, this yard is divided into two equal operating areas, and, in each one, a crane is placed, and it is equipped with reach stackers to enable container moves across both operating areas. However, this policy causes poor scheduling of crane moves, because it gives rise to many crane interference situations. For the sake of minimizing the occurrence of these undesirable situations, this paper proposes a multi-agent simulation model including an improved strategy for crane scheduling. This strategy is inspired by the ant colony approach and it is governed by a new configuration for the rail yard's working area that eliminates the use of reach stackers. The proposed simulation model is based on two planner agents, to each of which a time-horizon planning is assigned. The simulation results show that the model developed here is very successful in significantly reducing unproductive times and moves (undesirable situations), and it outperforms other existing simulation models based on the current organizational policy.
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| 2. |
- Abourraja, Mohamed Nezar, et al.
(författare)
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An improving agent-based engineering strategy for minimizing unproductive situations of cranes in a rail–rail transshipment yard
- 2018
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Ingår i: Simulation. - : SAGE Publications. - 0037-5497 .- 1741-3133. ; 94:8, s. 681-705
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays, seaports seek to achieve a better massification (massive transportation of containers) share of their hinterland transport by promoting rail and river connections in order to more rapidly evacuate increasing container traffic shipped by sea and to avoid landside congestion. The attractiveness of a seaport to shipping enterprises depends not only on its reliability and nautical qualities but also on its massified hinterland connection capacity. Contrary to what has been observed in Europe, the massification share of Le Havre seaport has stagnated in recent years. To overcome this situation, Le Havre Port Authority is putting into service a multimodal hub terminal linked only with massified modes. In this study, we focus on rail–rail transshipment of this new terminal, specifically on minimizing unproductive situations of cranes to improve crane productivity and to speed up freight train processing. To this end, an improving agent-based engineering strategy called the “crane anti-collision strategy” is proposed and tested using multi-method simulation software (Anylogic). In a numerical study, the simulation results reveal that our developed model is very satisfactory and outperforms other existing simulation models.
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| 3. |
- Samiri, Mohamed Yassine, et al.
(författare)
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APRICOIN : An adaptive approach for prioritizing high-risk containers inspections
- 2017
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 5, s. 18238-18249
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Tidskriftsartikel (refereegranskat)abstract
- Risk evaluation of the containers remains a difficult task, often due to incomplete or ambiguous information on containers. In addition, the evaluation process needs to be adapted on an ongoing basis to cope with emerging risk factors. Furthermore, high-risk container inspection is commonly hindered by a low inspection capacity, which leads to a major issue: how can we prioritize the container inspection if the number of suspect containers exceeds the inspection capacity? Container inspection prioritizing may be the answer. In this paper, we propose a novel approach for adaptively prioritizing container inspection (APRICOIN). First, we enhance the container information flow to alleviate the problem of incomplete information by proposing an enhanced container descriptive. Second, we introduce the APRICOIN algorithm, which combines frequent pattern mining and a fuzzy logic system, to assess the container’s risk score. The frequent pattern growth algorithm is proposed to retrieve the key criteria for evaluating container risk. This is done through mining frequent criteria sets within the historic data set of container inspections by customs. The mined frequent criteria sets are used to assess fuzzy inference rules which are periodically readjusted to integrate new key criteria. Thereafter, the fuzzy logic system uses the obtained fuzzy inference rules to calculate a container’s risk score. Our major contribution consists of providing a new adaptive approach for assessing a container’s risk through combining frequent criteria mining and fuzzy logic. An illustrative study and a comparison with alternative approaches are performed to validate the proposed algorithm.
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