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Frank Meisel

Researcher at University of Kiel

Publications -  76
Citations -  3396

Frank Meisel is an academic researcher from University of Kiel. The author has contributed to research in topics: Computer science & Berth allocation problem. The author has an hindex of 22, co-authored 66 publications receiving 2715 citations. Previous affiliations of Frank Meisel include Martin Luther University of Halle-Wittenberg.

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A survey of berth allocation and quay crane scheduling problems in container terminals

TL;DR: New classification schemes for berth allocation problems and quay crane scheduling problems are developed and particular focus is put on integrated solution approaches which receive increasing importance for the terminal management.
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A follow-up survey of berth allocation and quay crane scheduling problems in container terminals

TL;DR: This paper classify this new literature according to the features of models considered for berth allocation, quay crane scheduling and integrated approaches by using the classification schemes proposed in the preceding survey.
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The home health care routing and scheduling problem with interdependent services.

TL;DR: A planning approach for the daily planning of health care services carried out at patients’ homes by staff members of a home care company is proposed, which can be used for optimizing economical and service oriented measures of performance.
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Heuristics for the Integration of Crane Productivity in the Berth Allocation Problem

TL;DR: In this paper, the authors investigated the combined problem of berth allocation and crane assignment in container terminals, which includes important real world aspects such as the decrease of marginal productivity of quay cranes assigned to a vessel and the increase in handling time if vessels are not berthed at their desired position at the quay.
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A fast heuristic for quay crane scheduling with interference constraints

TL;DR: A revised optimization model for the scheduling of quay cranes is presented and a heuristic solution procedure is proposed for searching a subset of above average quality schedules which produces much better solutions in considerably shorter run times than all algorithms known from the literature.