Optimally scheduling interfering and non‐interfering cranes

Emde, Simon

doi:10.1002/nav.21768

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…Based on the current literature, the QCs restrictions include safety distance between two QCs, movement limitations, and interference among QCs [20]. The QCs are rubber-tired at some MCTs and rail-mounted on others [21]. The rubber-tired QCs (also known as moveable QCs) can move freely and cross each other, while the latter cannot [22].…”

Section: Seaside Operationsmentioning

confidence: 99%

A survey on computational intelligence approaches for intelligent marine terminal operations

Aslam,

Michaelides,

Herodotou

2024

IET Intelligent Trans Sys

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Marine container terminals (MCTs) play a crucial role in intelligent maritime transportation (IMT) systems. Since the number of containers handled by MCTs has been increasing over the years, there is a need for developing effective and efficient approaches to enhance the productivity of IMT systems. The berth allocation problem (BAP) and the quay crane allocation problem (QCAP) are two well‐known optimization problems in seaside operations of MCTs. The primary aim is to minimize the vessel service cost and maximize the performance of MCTs by optimally allocating berths and quay cranes to arriving vessels subject to practical constraints. This study presents an in‐depth review of computational intelligence (CI) approaches developed to enhance the performance of MCTs. First, an introduction to MCTs and their key operations is presented, primarily focusing on seaside operations. A detailed overview of recent CI methods and solutions developed for the BAP is presented, considering various berthing layouts. Subsequently, a review of solutions related to the QCAP is presented. The datasets used in the current literature are also discussed, enabling future researchers to identify appropriate datasets to use in their work. Eventually, a detailed discussion is presented to highlight key opportunities along with foreseeable future challenges in the area.

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Section: Seaside Operationsmentioning

confidence: 99%

A survey on computational intelligence approaches for intelligent marine terminal operations

Aslam,

Michaelides,

Herodotou

2024

IET Intelligent Trans Sys

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“…Unlike classic Benders decomposition, we do not re-solve the master model from scratch whenever a new cut is added, but instead inject cuts into the branch & cut tree as it evolves as lazy constraints. This approach is often called branch & Benders cut (Rahmaniani et al, 2017, Emde, 2017. Moreover, we do not employ classic Benders cuts but instead use combinatorial logic-based cuts in the spirit of Codato and Fischetti (2006) and Hooker (2011).…”

Section: Logic-based Benders Decompositionmentioning

confidence: 99%

Logic-based benders decomposition for scheduling a batching machine

Emde

Polten

Gendreau

2020

Computers & Operations Research

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“…The search terminates as soon as there are no more feasible, unexplored nodes left. This approach is sometimes referred to as "branch and Benders cut" (Emde 2017a;Rahmaniani et al 2017).…”

Section: Branch and Benders Cut For Jitaspmentioning

confidence: 99%

Sequencing assembly lines to facilitate synchronized just-in-time part supply

Emde

Polten

2019

J Sched

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The problem of sequencing assembly lines consists of determining the order in which a given set of products is launched down the line. Since individual products may require different parts in different quantities, the production sequence has a big influence on line-side inventory. Classically, sequences are often optimized with the goal of attaining level schedules, i.e., the part demand should be smooth during the planning horizon. However, this approach does not necessarily work well if parts are delivered at discrete points in time in bulk quantities. In this paper, we consider a production system where bins of parts are delivered periodically by a tow train from a central depot at fixed times. Due to the limited space at the assembly line, the maximum number of bins in stock at any time at any station should be minimal. We propose an exact solution method based on combinatorial Benders decomposition as well as bounding procedures and heuristics for this problem. The algorithms are shown to perform well both on instances from the literature and on new data sets. We also investigate whether classic level scheduling methods are effective at reducing line-side stock in an assembly system supplied by tow train, and to what degree line-side stock can be traded off for more frequent deliveries.

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Optimally scheduling interfering and non‐interfering cranes

Cited by 7 publications

References 31 publications

A survey on computational intelligence approaches for intelligent marine terminal operations

A survey on computational intelligence approaches for intelligent marine terminal operations

Logic-based benders decomposition for scheduling a batching machine

Sequencing assembly lines to facilitate synchronized just-in-time part supply

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