D
David Pisinger
Researcher at Technical University of Denmark
Publications - 175
Citations - 12726
David Pisinger is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Knapsack problem & Network planning and design. The author has an hindex of 45, co-authored 175 publications receiving 10799 citations. Previous affiliations of David Pisinger include University of Copenhagen & University of Copenhagen Faculty of Science.
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Approximation algorithms for knapsack problems with cardinality constraints
TL;DR: The main ideas contained in the PTAS are used to derivePTAS's for the knapsack problem and its multi-dimensional generalization which improve on the previously proposed PTAS's.
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An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones
TL;DR: In this article, a mathematical model is formulated, defining a problem similar to the Flying Sidekick Traveling Salesman Problem, but for the capacitated multiple-truck case with time limit constraints and minimizing cost as objective function.
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Exact Solution of the Quadratic Knapsack Problem
TL;DR: An exact branch-and-bound algorithm is proposed for QKP, where upper bounds are computed by considering a Lagrangian relaxation that is solvable through a number of (continuous) knapsack problems, and the algorithm is capable of solving reasonable-size Max Clique instances from the literature.
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Liner shipping hub network design in a competitive environment
TL;DR: A mixed integer programming formulation is proposed for hub- and-spoke network design in a competitive environment that addresses the competition between a newcomer liner service provider and an existing dominating operator, both operating on hub-and-spokes networks.
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Using Decomposition Techniques and Constraint Programming for Solving the Two-Dimensional Bin-Packing Problem
David Pisinger,Mikkel M. Sigurd +1 more
TL;DR: This work proposes an algorithm based on the well-known Dantzig-Wolfe decomposition where the master problem deals with the production constraints on the rectangles while the subproblem deal with the packing of rectangles into a single bin and generates valid inequalities in a branch-and-cut system.