| 1. |
- 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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A simulation-based decision support framework devoted to Ro-Ro terminals : Design, implementation and evaluation
- 2023
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Ingår i: Computers & industrial engineering. - : Elsevier BV. - 0360-8352 .- 1879-0550. ; 180, s. 109248-
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Tidskriftsartikel (refereegranskat)abstract
- As a type of intermodal terminal, pure Ro-Ro terminals are one of the most important logistic hubs in the supply chain for rolling freight stored in containerized and wheeled steel boxes. These large-scale systems are highly complex, with nonlinear and hard-to-predict behavior evolving in a stochastic environment. Consequently, making decisions about any problem thereof is no mean feat, particularly for terminal planners. To assist them in decision-making, a pool of relevant models and tools have been developed over the years in the literature. Nevertheless, models that are oriented toward specific objectives dominate, and generic ones are rare. This paper tries to fill this gap and proposes a generic framework to be used as a factory to create specific decision support models based on simulation for pure Ro-Ro terminals. This framework is formulated following two artifacts: (1) the known classification of key performance indicators combined with the typical functional and physical organization of pure Ro-Ro terminals; (2) the three main arteries of harbor systems, namely flows, decisions and operations. Then a scalable way of making decisions based on a flexible form of the cost function weighted according to a set of coefficients is integrated. These designed coefficients allow decision-makers a wide flexibly in choosing how the best solutions are determined. An application of this framework is illustrated through a real case study, where the weights are estimated using an expert-profiling based approach then pushed into the OptQuest optimizer to be calibrated before analyzing the results. These results are aggregated, then expressed as scores on a scale of 0 to 1. This is to help terminal planners to easily identify the worst and best planning scenarios as well as the relationships and compatibilities between the involved handling rules to suggest different alternatives for managing operations.
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| 3. |
- Rouky, Naoufal, et al.
(författare)
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Simulation optimization based ant colony algorithm for the uncertain quay crane scheduling problem
- 2019
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Ingår i: International Journal of Industrial Engineering Computations. - : Growing Science. - 1923-2926 .- 1923-2934. ; 10:1, s. 111-132
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Tidskriftsartikel (refereegranskat)abstract
- This work is devoted to the study of the Uncertain Quay Crane Scheduling Problem (QCSP), where the loading /unloading times of containers and travel time of quay cranes are considered uncertain. The problem is solved with a Simulation Optimization approach which takes advantage of the great possibilities offered by the simulation to model the real details of the problem and the capacity of the optimization to find solutions with good quality. An Ant Colony Optimization (ACO) meta-heuristic hybridized with a Variable Neighborhood Descent (VND) local search is proposed to determine the assignments of tasks to quay cranes and the sequences of executions of tasks on each crane. Simulation is used inside the optimization algorithm to generate scenarios in agreement with the probabilities of the distributions of the uncertain parameters, thus, we carry out stochastic evaluations of the solutions found by each ant. The proposed optimization algorithm is tested first for the deterministic case on several well-known benchmark instances. Then, in the stochastic case, since no other work studied exactly the same problem with the same assumptions, the Simulation Optimization approach is compared with the deterministic version. The experimental results show that the optimization algorithm is competitive as compared to the existing methods and that the solutions found by the Simulation Optimization approach are more robust than those found by the optimization algorithm.
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