Back to Search
Start Over
Multi-objective simulation optimization for complex urban mass rapid transit systems
- Source :
- Annals of Operations Research. 305:449-486
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- In this paper, we present a multi-objective simulation-based headway optimization for complex urban mass rapid transit systems. Real-world applications often confront conflicting goals of cost versus service level. We propose a two-phase algorithm that combines the single-objective covariance matrix adaptation evolution strategy with a problem-specific multi-directional local search. With a computational study, we compare our proposed method against both a multi-objective covariance matrix adaptation evolution strategy and a non-dominated sorting genetic algorithm. The integrated discrete event simulation model has several stochastic elements. Fluctuating demand (i.e., creation of passengers) is driven by hourly origin-destination-matrices based on mobile phone and infrared count data. We also consider the passenger distribution along waiting platforms and within vehicles. Our two-phase optimization scheme outperforms the comparative approaches, in terms of both spread and the accuracy of the resulting Pareto front approximation.
- Subjects :
- Mathematical optimization
Population-based algorithms
Computer science
Multi-directional local search
0211 other engineering and technologies
General Decision Sciences
Public transportation
02 engineering and technology
Management Science and Operations Research
Multi-objective optimization
0502 economics and business
Headway
Genetic algorithm
Local search (optimization)
Discrete event simulation
CMA-ES
Headway optimization
050210 logistics & transportation
021103 operations research
Transit network frequencies setting problem
business.industry
05 social sciences
Sorting
Simulation optimization
Evolution strategy
business
Subjects
Details
- ISSN :
- 15729338 and 02545330
- Volume :
- 305
- Database :
- OpenAIRE
- Journal :
- Annals of Operations Research
- Accession number :
- edsair.doi.dedup.....1a591547f1ee8d87c56a3e1194d8e8ae