Paper Info
Title
A Hyperheuristic Approach for Location-Routing Problem of Cold Chain Logistics considering Fuel Consumption
Abstract
In response to violent market competition and demand for low-carbon economy, cold chain logistics companies have to pay attention to customer satisfaction and carbon emission for better development. In this paper, a biobjective mathematical model is established for cold chain logistics network in consideration of economic, social, and environmental benefits; in other words, the total cost and distribution period of cold chain logistics are optimized, while the total cost consists of cargo damage cost, refrigeration cost of refrigeration equipment, transportation cost, fuel consumption cost, penalty cost of time window, and operation cost of distribution centres. One multiobjective hyperheuristic optimization framework is proposed to address this multiobjective problem. In the framework, four selection strategies and four acceptance criteria for solution set are proposed to improve the performance of the multiobjective hyperheuristic framework. As known from a comparative study, the proposed algorithm had better overall performance than NSGA-II. Furthermore, instances of cold chain logistics are modelled and solved, and the resulting Pareto solution set offers diverse options for a decision maker to select an appropriate cold chain logistics distribution network in the interest of the logistics company.
Year
DOI
Venue
2020
10.1155/2020/8395754
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
Field
DocType
Volume
Customer satisfaction,Computer science,Operations research,Cold chain,Solution set,Artificial intelligence,Fuel efficiency,Acceptance testing,Total cost,Machine learning,Decision maker,Market competition
Journal
2020.0
ISSN
Citations 
PageRank 
1687-5265
0
0.34
References 
Authors
14
5
Name
Order
Citations
PageRank
Zheng Wang100.34
Longlong Leng200.68
Shun Wang300.34
Gongfa Li421.77
Yanwei Zhao53513.48