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Solving the Container Relocation Problem by Using a Metaheuristic Genetic Algorithm (CROSBI ID 313179)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Gulić, Marko ; Maglić, Livia ; Krljan, Tomislav ; Maglić, Lovro Solving the Container Relocation Problem by Using a Metaheuristic Genetic Algorithm // Applied sciences (Basel), 12 (2022), 15; 7397, 24. doi: 10.3390/app12157397

Podaci o odgovornosti

Gulić, Marko ; Maglić, Livia ; Krljan, Tomislav ; Maglić, Lovro

engleski

Solving the Container Relocation Problem by Using a Metaheuristic Genetic Algorithm

Maritime transport is the backbone of international trade of goods. Therefore, seaports are of great importance for maritime transport. Container transport plays an important role in maritime transport and is increasing year by year. Containers transported to a container terminal are stored in container yards side by side and on top of each other, forming blocks. If a container that is not on top of the block has to be retrieved, the containers that are above the required container must be relocated before the required container is retrieved. These additional container relocations, which block the retrieval of the required container, slow down the entire retrieval process. The container relocation problem, also known as the block relocation problem, is an optimization problem that involves finding an optimal sequence of operations for retrieving blocks (containers) from a container yard in a given order, minimizing additional relocations of blocking containers. In this paper, the focus is on the two-dimensional, static, offline and the restricted container relocation problem of real-size yard container bays. A new method for resolving the container relocation problem that uses a genetic algorithm is proposed to minimize the number of relocations within the bay. The method is evaluated on well-known test instances, and the obtained results are compared with the results of various relevant models for resolving the container relocation problem. The results show that the proposed method achieves the best or the second-best result for each test instance within the test se

container yard bay ; container relocation problem ; optimization problem ; genetic algorith

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Podaci o izdanju

12 (15)

2022.

7397

24

objavljeno

2076-3417

10.3390/app12157397

Trošak objave rada u otvorenom pristupu

Povezanost rada

Interdisciplinarne tehničke znanosti, Računarstvo, Tehnologija prometa i transport

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