Developing equilibrium optimization methods for hub location problems
Gespeichert in:
Verfasser / Beitragende:
[Kai Yang, Yankui Liu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/8(2015-08-01), 2337-2353
Format:
Artikel (online)
Online Zugang:
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605470235 | ||
| 003 | CHVBK | ||
| 005 | 20210128100326.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150801xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1427-1 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1427-1 | ||
| 245 | 0 | 0 | |a Developing equilibrium optimization methods for hub location problems |h [Elektronische Daten] |c [Kai Yang, Yankui Liu] |
| 520 | 3 | |a This paper develops three new equilibrium optimization models for $$p$$ p -hub center problem, in which the travel times are characterized by fuzzy random variables. The proposed equilibrium optimization methods are to find the locations of hub facilities and demand nodes so as to maximize equilibrium service levels of uncertain travel times. Under mild assumptions, we first handle equilibrium service levels and reduce them to their equivalent probability constraints. According to structural characteristics of equivalent stochastic programming models, we design a new parametric decomposition-based hybrid tabu search (PD-HTS) algorithm that incorporates parametric decomposition (PD), sample average approximation and tabu search algorithm. To demonstrate the effectiveness of designed solution method, we conduct some numerical experiments by using Australian Post data set and randomly generated data set. The comparison study shows that the PD-HTS algorithm exhibits better performance than the parametric decomposition-based hybrid genetic algorithm. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Hub location problem |2 nationallicence | |
| 690 | 7 | |a Equilibrium service level |2 nationallicence | |
| 690 | 7 | |a Stochastic programming |2 nationallicence | |
| 690 | 7 | |a Parametric decomposition |2 nationallicence | |
| 690 | 7 | |a Sample average approximation |2 nationallicence | |
| 690 | 7 | |a Tabu search algorithm |2 nationallicence | |
| 700 | 1 | |a Yang |D Kai |u Risk Management and Financial Engineering Lab, College of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, China |4 aut | |
| 700 | 1 | |a Liu |D Yankui |u Risk Management and Financial Engineering Lab, College of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/8(2015-08-01), 2337-2353 |x 1432-7643 |q 19:8<2337 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1427-1 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1427-1 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yang |D Kai |u Risk Management and Financial Engineering Lab, College of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Liu |D Yankui |u Risk Management and Financial Engineering Lab, College of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/8(2015-08-01), 2337-2353 |x 1432-7643 |q 19:8<2337 |1 2015 |2 19 |o 500 | ||