Journal article
Optimization of facility location and size problem based on bi-level multi-objective programming
Computers & operations research, v 145, 105860
Sep 2022
Abstract
With the rapid urbanization, solving the facility location and size problem (FLSP) of general service infrastructure (GSI) has become an essential issue in spatial planning. Due to unreasonable location and regional scale, the satisfaction of residents has been seriously affected. This paper develops a bi-level multi-objective programming (BLMOP) to optimize both facility location and size. Three major problems have been addressed: (1) solving the contradiction between supply and demand; (2) keeping a balance of social, economic, and environmental benefits; and (3) designing a multi-objective particle swarm optimization (MOPSO) algorithm by modifying the parameters and learning strategies. To obtain feasible solutions, a combination of optimistic and pessimistic approaches is adopted. Taking the rural areas of Southwest China as an example, the results find that the proposed model enables to provide objective-oriented optimization schemes depending on the decision-maker’s (DM) preferences. Furthermore, the MOPSO algorithm can solve the BLMOP and provide Pareto-optimal solutions separately.
•FLSP is optimized by balancing supply and demand.•Trade-offs between social, economic, and environmental impacts in FLSP are addressed.•MOPSO algorithm is designed to solve nonlinear bi-level programming.•Objective-oriented FLSP schemes are obtained depending on DMs’ preferences.
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Details
- Title
- Optimization of facility location and size problem based on bi-level multi-objective programming
- Creators
- Zhineng Hu - Sichuan UniversityLi Wang - Sichuan UniversityJindong Qin - Wuhan University of TechnologyBenjamin Lev - Drexel UniversityLu Gan - Sichuan University
- Publication Details
- Computers & operations research, v 145, 105860
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000808130500006
- Scopus ID
- 2-s2.0-85130574407
- Other Identifier
- 991019169617204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Industrial
- Operations Research & Management Science