Solving the Integrated Multi-Port Stowage Planning and Container Relocation Problems with a Genetic Algorithm and Simulation (original) (raw)
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arXiv: Optimization and Control, 2020
This paper introduces a new optimization model that integrates the multi-port stowage planning problem with the container relocation problem. This problem is formulated as a binary mathematical programming model that must find the containers' move sequence so that the number of relocations during the whole journey of a ship, as well as the associated port yards is minimized. Modeling by binary variables to represent the cargo status in a ship and yards makes the problem very complex to be solved by exact methods. To the best of our knowledge, this integrated model has not been developed yet as that such problems are always addressed in a partitioned or hierarchical way. A demonstration of the benefits of an integrated approach is given. The model is solved in two different commercial solvers and the results for randomly generated instances are presented and compared to the hierarchical approach. Two heuristics approaches are proposed to quickly generate feasible solutions for wa...
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The relocation of containers is a crucial operation in container ports all around the world. The Container Relocation Problem (CRP) is focused upon to find a sequence of container retrievals in a defined order from a single yard container bay with a minimum number of relocations. The goal of this paper is to find out if Genetic Algorithm (GA) can give new insights in the problem of solving the CRP. In this paper we focus on the two-dimensional, static, offline and restricted CRP of real-world yard container bays. Four rules are proposed for determining the position of relocated containers. We applied GA to find the best sequence of container retrievals according to these four rules in order to minimize the number of relocations within the bay. The experimental testing was run on a total of 800 different instances with varying bay sizes and number of containers. The given results are compared with the results of different authors using other heuristic methods. The results show that the proposed model solves CRP and achieves near optimal solutions.
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Short sea shipping is prone to be one of the areas of development for the transportation policy of the European Union in the near future. Nevertheless, in order to be able to make its stand on the market, there are several problems that have to addressed, namely its safety and economic viability. To study the second, a genetic algorithm may
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The purpose of this study is to develop an efficient heuristic for solving the stowage problem. Containers on board a container ship are stacked one on top of the other in columns, and can only be unloaded from the top of the column. A key objective of stowage planning is to minimize the number of container movements. A genetic algorithm technique is used for solving the problem. A compact and efficient encoding of solutions is developed, which reduces significantly the search space. The efficiency of the suggested encoding is demonstrated through an extensive set of simulation runs and its flexibility is demonstrated by successful incorporation of ship stability constraints.
Solving the Container Relocation Problem by Using a Metaheuristic Genetic Algorithm
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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 fo...
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The Journal of Japan Institute of Navigation, 2008
Container is a standard in worldwide transportation method, which is capable ofbeing moved by sea, road or rail with relative simplicity. Due to the continuously increasing container trade, many container terminals as well as liner shipping companies are presently frustrating to sborten the turnaround time of a ship for fimancial savings. Therefore. any methDds to improve the containership stowage process would be significant This paper examines the effectiyeness of colltainer amngements in order to evaluate hDw to optimize the stowage plan which was established at the present port and associated with the unloading plan at next port, The efficient of the ship stowage plan is evaluated by the minimllm number of rehandled container required arid the maximum value of ship stability obtained during to trip from the present port to the next port The genetic algorithn is empioyed as a heur istic for the appToximately optimized solutions and the validation of the proposed approach is performed with some computational experiments. Kbywords: Containership handling; Container 1lermina4' Genetic Algorithm; Logistics JapanInstitute of 119g Navigation An Investigation into Effeetiveness of Container Arrangements on Optimizing a Containership Stowage Plan
Solving inland container ship stowage planning problem on full route through a two-phase approach
International Journal of Shipping and Transport Logistics, 2020
Inland container ship emphasises capacity utilisation due to its limited capacity. Its stability is very sensitive to the stowage plan. The shipping line planners are under pressure to make efficient stowage plan on full route. This paper adopts a two-phase approach to separate the problem into two planning levels: multi-port master bay plan problem (MP-MBPP) on full route and slot plan problem (SPP) for each bay at each port. The mathematical models are proposed respectively for both sub-problems based on mixed integer programming. For each sub-problem, the greedy randomised adaptive search procedure (GRASP) and the heuristic evolutionary strategy (HES) algorithm are proposed, respectively. The grey entropy parallel analysis (GEPA) method is presented to guide HES in multi-objective optimisation. Experimental results based on real-world scenarios are presented to show the efficacy of proposed algorithms and method.
The Terminal-Oriented Ship Stowage Planning Problem
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The Ship Stowage Planning Problem is the problem of determining the optimal position of containers to be stowed in a containership. In this paper we address the problem considering the objectives of the terminal management that are mainly related to the yard and transport operations. We propose a Binary Integer Program and a two-step heuristic algorithm. An extensive computational experience shows the efficiency and effectiveness of our approach. A classification scheme for stowage planning problems is also provided.
Stowage and Transport Optimization in Ship Planning
Online Optimization of Large Scale Systems, 2001
We consider the ship planning problem at maritime container terminals where containers are loaded onto and discharged from ships using quay cranes. The container transport between the ships and the yard positions in the terminal is carried out by a fleet of straddle carriers. Based on a stowage plan provided by the shipping company, the dispatcher assigns containers to specified bay positions. Then, subject to operational and stability constraints, he schedules containers in order to avoid waiting times at the quay cranes. We propose an approach combining stowage planning and the selection of "good" loading and transport sequences. For a just-in-time scheduling model, we present computational results based on real-world data of a German container terminal. Moreover, we discuss some real-time and online influences on the daily dispatch situation.