An Integrated Optimization Model for the Multi-Port Stowage Planning and the Container Relocation Problems (original) (raw)
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The Terminal-Oriented Ship Stowage Planning Problem
European Journal of Operational Research, 2014
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 planning for container ships to reduce the number of shifts
Annals of Operations Research, 1998
This paper deals with a stowage plan for containers in a container ship. Containers on board a container ship are placed in vertical stacks, located in many bays. Since the access to the containers is only from the top of the stack, a common situation is that containers designated for port J must be unloaded and reloaded at port I (before J) in order to access containers below them, designated for port I. This operation is called "shifting". A container ship calling at many ports may encounter a large number of shifting operations, some of which can be avoided by efficient stowage planning. In general, the stowage plan must also take into account stability and strength requirements, as well as several other constraints on the placement of containers. In this paper, we only deal with stowage planning in order to minimize the number of shiftings, without considering stability and several other constraints. First, we briefly present a 0 -1 binary linear programming formulation that can find the optimal solution for stowage planning. However, finding the optimal solution using this model is quite limited because of the large number of binary variables and constraints needed for the formulation. Moreover, in [3] the stowage planning problem is shown to be NPcomplete. For these reasons, the Suspensory Heuristic Procedure was developed.
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.
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.
Journal of the Operational Research Society, 2019
The relatively limited capacities of inland container liner shipping mean that, unlike in maritime container shipping, capacity utilisation is more important than scheduling. Capacity utilisation and stability must be considered in the stowage planning problem in inland container liner shipping. We adopt a multi-stage hierarchical decomposition approach to decompose the problem into multiple stages because a ship needs to visit multiple ports during its voyage. At each stage, the stowage planning problem of the current port is decomposed hierarchically into two sub-problems: the master bay planning problem (MBPP) and slot planning problem (SPP). The multi-port MBPP is first optimised to simultaneously generate the master bay plans for multiple ports over the full route. This approach incorporates two heuristic algorithms, a greedy randomised adaptive search procedure for the multi-port MBPP, and a heuristic evolutionary strategy algorithm for the SPP. Computational results for randomly generated data corresponding to real-size scenarios of inland container ships are presented validating the proposed algorithms.
A Mathematical Model for the Container Stowage and Ship Routing Problem
Journal of Mathematical Modelling and Algorithms in Operations Research, 2012
The main goal of this paper is to present a mathematical model for a fleet of containerships with no pre-defined routes, considering demands and delivery deadlines and overstowing prevention. The objective is to minimize the total distribution cost in the contest of the short sea shipping. The short sea shipping is a very complex problem that belongs to the class of routing problems, more precisely, to the Capacitated Vehicle Routing Problem with deadlines and loading constraints. In this problem two major decisions must be made: which ports should be visited by each vessel and the related visit sequence, and where to load the containers in vessels in order to prevent overstowing. A mixed integer programming model for the problem is presented and solved. This mathematical formulation intends to contribute to a better management of small fleets of containerships in order to reduce transportation time and delivering costs.
A genetic algorithm with a compact solution encoding for the container ship stowage problem
2002
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.
A mathematical formulation and efficient heuristics for the dynamic container relocation problem
Naval Research Logistics (NRL), 2014
The container relocation problem (CRP) is concerned with emptying a single yard‐bay which contains J containers each following a given pickup order so as to minimize the total number of relocations made during their retrieval process. The CRP can be modeled as a binary integer programming (IP) problem and is known to be NP‐hard. In this work, we focus on an extension of the CRP to the case where containers are both received and retrieved from a single yard‐bay, and call it the dynamic container relocation problem. The arrival (departure) sequences of containers to (from) the yard‐bay is assumed to be known a priori. A binary IP formulation is presented for the problem. Then, we propose three types of heuristic methods: index based heuristics, heuristics using the binary IP formulation, and a beam search heuristic. Computational experiments are performed on an extensive set of randomly generated test instances. Our results show that beam search heuristic is very efficient and perform...