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Transportation Optimization Models for Intermodal Networks with Fuzzy Node Capacity, Detour Factor, and Vehicle Utilization Constraints
- Source :
- Mathematics, Vol 8, Iss 2109, p 2109 (2020), Mathematics; Volume 8; Issue 12; Pages: 2109
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- This paper develops a mathematical model for intermodal freight transportation. It focuses on determining the flow of goods, the number of vehicles, and the transferred volume of goods transported from origin points to destination points. The model of this article is to minimize the total cost, which consists of fixed costs, transportation costs, intermodal transfer costs, and CO2 emission costs. It presents a mixed integer linear programming (MILP) model that minimizes total costs, and a fuzzy mixed integer linear programming (FMILP) model that minimizes imprecise total costs under conditions of uncertain data. In the models, node capacity, detour, and vehicle utilization are incorporated to estimate the performance impact. Additionally, a computational experiment is carried out to evaluate the impact of each constraint and to analyze the characteristics of the models under different scenarios. Developed models are tested using real data from a case study in Southern Vietnam in order to demonstrate their effectiveness. The results indicate that, although the objective function (total cost) increased by 20%, the problem became more realistic to address when the model was utilized to solve the constraints of node capacity, detour, and vehicle utilization. In addition, on the basis of the FMILP model, fuzziness is considered in order to investigate the impact of uncertainty in important model parameters. The optimal robust solution shows that the total cost of the FMILP model is enhanced by 4% compared with the total cost of the deterministic model. Another key measurement related to the achievement of global sustainable development goals is considered, reducing the additional intermodal transfer cost and the cost of CO2 emissions in the objective function.
- Subjects :
- intermodal transportation
Mathematical optimization
Total cost
Computer science
General Mathematics
02 engineering and technology
node capacity
Fuzzy logic
CO2 emissions
0502 economics and business
0202 electrical engineering, electronic engineering, information engineering
Computer Science (miscellaneous)
terminal congestion
Fixed cost
Engineering (miscellaneous)
Integer programming
Constraint (mathematics)
050210 logistics & transportation
Uncertain data
detour
vehicle utilization
Node (networking)
lcsh:Mathematics
05 social sciences
lcsh:QA1-939
mixed integer programming
fuzzy constraint
cost minimization
Key (cryptography)
020201 artificial intelligence & image processing
Subjects
Details
- Language :
- English
- ISSN :
- 22277390
- Volume :
- 8
- Issue :
- 2109
- Database :
- OpenAIRE
- Journal :
- Mathematics
- Accession number :
- edsair.doi.dedup.....0b9c1d649bed25bb5367b237e67663da