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Peer-reviewedCC BY-NC-NDComputer Aided Civil and Infrastructure Engineering

Dynamic planning of facility locations with benefits from multitype facility colocation

Abstract

This article presents a mixed-integer programming model for a multitype facility colocation problem with capacity expansion over a multiperiod horizon. This problem is motivated by the emerging U.S. biofuel industry that is rapidly expanding its infrastructure facilities to produce bioethanol from agricultural crops. Each type of facility (e.g., corn- or cellulose-based biorefinery) requires a different type of raw material (e.g., corn or perennial grass), but they produce the same final product (e.g., bioethanol), and colocation of multiple types of facilities results in cost-saving benefits due to complementary production process and byproduct recycling. Multiple solution approaches (i.e., Lagrangian relaxation, Benders decomposition, and accelerated Benders decomposition) are proposed to solve this problem. Numerical experiments show that accelerated Benders decomposition most effectively solves large-sized problems in a short amount of time. Various managerial insights are also drawn from the computational results.

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BibTeX
@article{xie2026dynamic,
  title = {{Dynamic planning of facility locations with benefits from multitype facility colocation}},
  author = {Weijun Xie and Yanfeng Ouyang},
  journal = {Computer Aided Civil and Infrastructure Engineering},
  year = {2026},
  month = oct,
  doi = {10.1111/mice.12034},
  url = {https://hal.science/hal-05783716v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Dynamic planning of facility locations with benefits from multitype facility colocation
AU  - Weijun Xie
AU  - Yanfeng Ouyang
PY  - 2026
DA  - 2026/10/07
JO  - Computer Aided Civil and Infrastructure Engineering
DO  - 10.1111/mice.12034
UR  - https://hal.science/hal-05783716v1
AB  - This article presents a mixed-integer programming model for a multitype facility colocation problem with capacity expansion over a multiperiod horizon. This problem is motivated by the emerging U.S. biofuel industry that is rapidly expanding its infrastructure facilities to produce bioethanol from agricultural crops. Each type of facility (e.g., corn- or cellulose-based biorefinery) requires a different type of raw material (e.g., corn or perennial grass), but they produce the same final product (e.g., bioethanol), and colocation of multiple types of facilities results in cost-saving benefits due to complementary production process and byproduct recycling. Multiple solution approaches (i.e., Lagrangian relaxation, Benders decomposition, and accelerated Benders decomposition) are proposed to solve this problem. Numerical experiments show that accelerated Benders decomposition most effectively solves large-sized problems in a short amount of time. Various managerial insights are also drawn from the computational results.
ER  -