Abstract
In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model, first of all, the objective function VaR is approximated through discretization method of fuzzy variables. Therefore, the original problem is converted to the task of a finite-dimensional optimization. Then, a hybrid heuristic algorithm integrating binary particle swarm optimization (BPSO), simplex algorithm and the approximation approach is designed to solve the location model. Finally, a numerical example is provided.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 |
| Pages | 43-46 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2010 |
| Event | 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen Duration: 2010 Dec 13 → 2010 Dec 15 |
Other
| Other | 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 |
|---|---|
| City | Shenzhen |
| Period | 10/12/13 → 10/12/15 |
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Keywords
- Binary particle swarm optimization
- Facility location
- Fuzzy variable
- Two-stage fuzzy programming
- Value at Risk
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Theoretical Computer Science
Cite this
A hybrid BPSO approach for fuzzy facility location problems with VaR. / Wang, Shuming; Watada, Junzo.
Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. p. 43-46 5715366.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A hybrid BPSO approach for fuzzy facility location problems with VaR
AU - Wang, Shuming
AU - Watada, Junzo
PY - 2010
Y1 - 2010
N2 - In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model, first of all, the objective function VaR is approximated through discretization method of fuzzy variables. Therefore, the original problem is converted to the task of a finite-dimensional optimization. Then, a hybrid heuristic algorithm integrating binary particle swarm optimization (BPSO), simplex algorithm and the approximation approach is designed to solve the location model. Finally, a numerical example is provided.
AB - In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model, first of all, the objective function VaR is approximated through discretization method of fuzzy variables. Therefore, the original problem is converted to the task of a finite-dimensional optimization. Then, a hybrid heuristic algorithm integrating binary particle swarm optimization (BPSO), simplex algorithm and the approximation approach is designed to solve the location model. Finally, a numerical example is provided.
KW - Binary particle swarm optimization
KW - Facility location
KW - Fuzzy variable
KW - Two-stage fuzzy programming
KW - Value at Risk
UR - http://www.scopus.com/inward/record.url?scp=79952566482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952566482&partnerID=8YFLogxK
U2 - 10.1109/ICGEC.2010.19
DO - 10.1109/ICGEC.2010.19
M3 - Conference contribution
AN - SCOPUS:79952566482
SN - 9780769542812
SP - 43
EP - 46
BT - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
ER -