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Pengyu Yan

Researcher at University of Electronic Science and Technology of China

Publications -  27
Citations -  456

Pengyu Yan is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Job shop scheduling & Computer science. The author has an hindex of 8, co-authored 21 publications receiving 324 citations. Previous affiliations of Pengyu Yan include Northwestern Polytechnical University & University of Technology of Troyes.

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Energy-efficient bi-objective single-machine scheduling with power-down mechanism

TL;DR: A single-machine scheduling problem with power-down mechanism to minimize both total energy consumption and maximum tardiness and a basic e − constraint method is proposed to obtain the complete Pareto front of the problem.
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A branch and bound algorithm for optimal cyclic scheduling in a robotic cell with processing time windows

TL;DR: A branch and bound algorithm is described for optimal cyclic scheduling in a robotic cell with processing time windows that could find an optimal solution by enumerating partial non-prohibited intervals by dividing these prohibited intervals into a series of subsets.
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A mixed integer programming approach for multi-cyclic robotic flowshop scheduling with time window constraints

TL;DR: This paper presents the first mixed integer programming (MIP) model for the multi-cyclic robotic flowshop scheduling problem based on the description and analysis of the problem and solves the model using commercial software CPLEX.
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Optimal cyclic scheduling of a hoist and multi-type parts with fixed processing times

TL;DR: In this paper, an exact algorithm to solve a cyclic hoist scheduling problem in a printed circuit board (PCB) electroplating facility, where multi-type parts with fixed processing times are processed in the same time and the parts are not allowed to wait in the tanks or on the hoist, is proposed.
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A dynamic scheduling approach for optimizing the material handling operations in a robotic cell

TL;DR: This paper investigates a real-time dynamic job-shop scheduling problem in a robotic cell, in which multiple jobs enter into the cell with unexpected arriving rates, and proposes an exact iterative algorithm, which starts with a relaxed solution of the MIP model and iteratively adds essential robot handling capacity constraints back to the relaxed Mip model until an optimal solution is found.