A Lagrangian-ACO matheuristic for car sequencing

In this study, we investigate a hybrid Lagrangian relaxation ant colony optimisation for optimisation version of the car sequencing problem. Several cars are required to be scheduled on an assembly line and each car requires a number of options such as sunroof and/or air conditioning. These cars are...

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Bibliographic Details
Published in:EURO journal on computational optimization 2014-11, Vol.2 (4), p.279-296
Main Authors: Thiruvady, Dhananjay, Ernst, Andreas, Wallace, Mark
Format: Article
Language:English
Subjects:
90B99
Air conditioning
Algorithms
Analysis
Ant colony optimisation
Ant colony optimization
Assembly lines
Automobile industry
Automobiles
Automotive engineering
Business and Management
Car sequencing
Feasibility
Heuristic
Hybrid methods
Information technology
Integer programming
Lagrange multiplier
Lagrangian relaxation
Management Science
Mathematical programming
Methods
Operations Management
Operations Research
Operations Research/Decision Theory
Optimization
Original Paper
Peer to peer computing
Pheromones
Scheduling
Sequencing
Studies
Sun roofs
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Summary:In this study, we investigate a hybrid Lagrangian relaxation ant colony optimisation for optimisation version of the car sequencing problem. Several cars are required to be scheduled on an assembly line and each car requires a number of options such as sunroof and/or air conditioning. These cars are required to be sequenced such that sub-sequences of specific sizes may only include a limited number of any option. While this is usually a hard constraint, in this study we treat it as a soft constraint and further require the utilisation of options be modulated across the sequence leading to the optimisation problem. We investigate various Lagrangian heuristics, ant colony optimisation (ACO) and hybrids of these methods. The results show that the Lagrangian-ACO hybrid is the best performing method for up to 300 cars.
ISSN:2192-4406
2192-4414
DOI:10.1007/s13675-014-0023-6