Kanxin Hu

ORCID: 0000-0003-1504-8982
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About
Contact & Profiles
Research Areas
  • Advanced Manufacturing and Logistics Optimization
  • Scheduling and Optimization Algorithms
  • Optimization and Packing Problems
  • Additive Manufacturing and 3D Printing Technologies
  • Manufacturing Process and Optimization
  • Assembly Line Balancing Optimization
  • Digital Transformation in Industry

National University of Singapore
2021-2024

Zhejiang University of Technology
2023-2024

Machines that simultaneously process jobs in a batch and sequentially handle batches are widely used additive manufacturing such as 3D printing. This paper is concerned with the job packing scheduling problem of single-batch-processing machine under two-dimensional geometric constraints (2D-SBPM). Existing researches for 2D-SBPM based on heuristic methods, which have unsatisfactory solution quality because repeated evaluations during habitual use original rules packing. To improve...

10.2139/ssrn.4714938 preprint EN 2024-01-01

Additive Manufacturing (AM), the technology of rapid prototyping directly from 3D digital models, has made a significant impact on both academia and industry. When facing growing demand AM services, production planning (AMPP) plays vital role in reducing makespan costs for service companies. This research focuses AMPP problem under unrelated machine environment two-dimensional irregular packing constraints such that can be minimized. Since there is no promising sub-second algorithm solving...

10.2139/ssrn.4221386 article EN SSRN Electronic Journal 2022-01-01

With the rapid growth in demand for additive manufacturing (AM) services, companies are facing increased pressure to produce irregularly shaped products tailored customer requirements. In this context, machine scheduling problems AM production planning drawing more attention with purpose of enhancing efficiency. This study focuses on unrelated parallel machines complex 2D irregular packing constraints, aiming minimize makespan. Both hole filling and free rotation considered process. Due...

10.2139/ssrn.4673689 preprint EN 2023-01-01
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