RESEARCH PAPER
An uncertain programming model for fixed charge transportation problem with item sampling rates
1
School of Mechanical Engineering, Jiangsu University of Technology, China
2
School of Automobile and Traffic Engineering, Jiangsu University of Technology, China
3
Department of public basic courses, Nanjing Institute of Industry Technology, China
Submission date: 2024-05-30
Final revision date: 2024-07-04
Acceptance date: 2024-08-08
Online publication date: 2024-08-11
Publication date: 2024-08-11
Corresponding author
Eksploatacja i Niezawodność – Maintenance and Reliability 2025;27(1):192165
HIGHLIGHTS
- Introduces two new parameters, productsampling pass rate and carbon emissions.
- The concepts of expected value model and chance-constrained model are proposed.
- A multi-objective analysis method and an improved sparrow algorithm are proposed.
- The performance of the improved sparrow algorithm is significantly improved.
KEYWORDS
TOPICS
ABSTRACT
This paper analyzes the transportation issue involving multiple objectives and items with fixed costs amid uncertainty, which aims to increase net profit while minimizing carbon emissions, to determine an optimal product shipping strategy. This paper introduces the use of uncertain theory to address the transportation dilemma, considering various challenges such as potential uncertainties during the actual transport process. It involves defining variables such as supply, demand and the rate of product sampling qualification as uncertain factors, constructing mathematical models, and deriving the corresponding model as well as the respective equivalent form by means of uncertainty theory. A linear weighted method is adopted to reflect the significance of each objective as identified by policymakers and suggest a sparrow optimization algorithm combined with butterfly search for numerical experiments to discover the optimal solution. This demonstrates the practicality and effectiveness of the proposed models.
ACKNOWLEDGEMENTS
This work was supported by The Natural Science Foundation of the Jiangsu Higher Education Institutions of China No：22KJD440001 and Changzhou Science&Technology Program No：CJ20220232.
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