Two-dimensional cut plan optimization for cutter suction dredgers


de Ruyter, Marcus J.M. (2009) Two-dimensional cut plan optimization for cutter suction dredgers University of Southampton, School of Civil Engineering and the Environment, Doctoral Thesis , 197pp.

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Description/Abstract

Optimal cut plans for cutter suction dredgers aim to maximize operational efficiency. Maximizing operational efficiency involves minimization of stoppage time resulting from non-productive dredger movements. To automate a systematic search for optimal twodimensional cut plans for cutter suction dredgers two models with an adaptive simulated annealing-based solution approach were developed.
The first model, the dredge cut nesting model, optimizes irregular stock cutting problems where stencils represent dredge cuts and sheets represent dredging areas. Stencils are collections of unit dredge cuts with dimensions related to an effective cutting width which can be achieved with the cutter suction dredger considered. The objectives of the dredge cut nesting model are to maximize sheet coverage and to minimize stencil overlap. Centroids of unit dredge cuts of final nest layouts are extracted and used as grid nodes in the second model.
The second model, the dredger routing model, optimizes asymmetric travelling salesperson problems with turning costs. The objectives of the dredger routing model are to minimize total route length and sum of turning angles, and to maximize average link length. A link consists of two or more route edges which are aligned with each other to within specified limits.
A significant result of this research is that an engineering application of both models showed that two-dimensional cut plans for cutter suction dredgers can be systematically optimized and that dredger routes with minimum turning costs can be found. However, results also showed that the dredger routing model is not yet sophisticated enough to find cut plans for cutter suction dredgers for which overall project execution time is minimal.

Item Type: Thesis (Doctoral)
Subjects:

Organisations: University of Southampton
ePrint ID: 79367
Date :
Date Event
April 2009Published
Date Deposited: 15 Mar 2010
Last Modified: 18 Apr 2017 20:15
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/79367

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