M
Machine Hsie
Researcher at National Chung Hsing University
Publications - 10
Citations - 469
Machine Hsie is an academic researcher from National Chung Hsing University. The author has contributed to research in topics: Schedule & Linear programming. The author has an hindex of 5, co-authored 9 publications receiving 380 citations.
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Mechanical properties of polypropylene hybrid fiber-reinforced concrete
TL;DR: In this paper, the authors investigated the mechanical properties of polypropylene hybrid fiber-reinforced concrete and showed that the compressive strength, splitting tensile strength, and flexural properties of the hybrid fiber reinforced concrete are better than the properties of single fiber-based concrete.
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Resource-constrained scheduling for continuous repetitive projects with time-based production units
TL;DR: In this paper, a scheduling model is presented to find the optimal set of production rates in different time periods for each crew, considering limited availability of resources, which addresses work continuity while maintaining lead-time and lead-distance between operations.
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A model used in creating a work-rest schedule for laborers
TL;DR: In this article, a GA-based mechanism was developed to search the Pareto front, which is one of the effective ways for solving multiobjective optimization problems, for constructing work-rest schedules for construction workers.
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Optimizing the Schedule of Dispatching Earthmoving Trucks through Genetic Algorithms and Simulation
TL;DR: In this paper, a discrete simulation model is applied to simulate earthmoving operations and generate schedules for dispatching various trucks, and the GAs are used as a filter to screen out schedules that require long trips.
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Modeling asphalt pavement overlay transverse cracks using the genetic operation tree and Levenberg-Marquardt Method
TL;DR: A novel approach, called ''LMGOT,'' that integrates two optimization techniques: the Levenberg-Marquardt (LM) Method and the genetic operation tree (GOT), which shows that the LMGOT is an efficient approach to building an accurate crack model.