JOURNAL ARTICLE

Cuckoo search algorithm for multi-objective supply chain problem

Fathy ElkazzazA. ATTIA MAHMOUDAli Maher

Year: 2018 Journal:   MATEC Web of Conferences Vol: 189 Pages: 06001-06001   Publisher: EDP Sciences

Abstract

A meta-heuristic algorithm called, the cuckoo search algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature to show the performance of the proposed model; in addition, the results have been compared to those achieved by the bee colony optimization algorithm and genetic algorithm. Those obtained results indicate that the proposed cuckoo search algorithm is able to get better Pareto solutions (non-dominated set) for the supply chain problem.

Keywords:
Cuckoo search Cuckoo Mathematical optimization Supply chain Genetic algorithm Computer science Pareto principle Pareto optimal Set (abstract data type) Algorithm Heuristic Metaheuristic Multi-objective optimization Mathematics Particle swarm optimization Business

Metrics

3
Cited By
0.50
FWCI (Field Weighted Citation Impact)
24
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Process Optimization and Integration
Physical Sciences →  Engineering →  Control and Systems Engineering

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