Paper Info
Title
A bi-criteria hybrid metaheuristic for analysing an integrated automotive supply chain.
Abstract
The automotive industry is one of the most important manufacturing sectors in the world due to its economic impact and technological complexities. While supply chain performance can have a dramatic impact on the automotive industry, there are multiple, often conflicting objectives that typically are used to optimize performance. We model the trade-off between cost and service level, and present a bi-criteria heuristic optimization methodology for a two-stage, integrated automotive supply chain. Our problem contains sequence-dependent setups on parallel machines and auxiliary resource assignments. We minimize the total cost of setups, inventory holding, and transportation costs, and the maximum percentage of outsourced parts per customer, simultaneously. We use our proposed method to solve a set of problem instances that are based on industrial data. Our proposed method generates approximate Pareto (efficient) solutions in a timely manner for use in practice.
Year
DOI
Venue
2016
10.1057/jors.2015.75
JORS
Keywords
Field
DocType
multi-objective,optimization,metaheuristic,encoding,decoding,supply chain
Heuristic,Economic impact analysis,Service level,Computer science,Operations research,Supply chain,Total cost,Pareto principle,Operations management,Automotive industry,Metaheuristic
Journal
Volume
Issue
ISSN
67
3
0160-5682
Citations 
PageRank 
References 
0
0.34
8
Authors
2
Name
Order
Citations
PageRank
Sherif A. Masoud100.34
Scott J. Mason255573.37