The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Product family modeling for mass customization
ICC&IE Selected papers from the 22nd ICC&IE conference on Computers & industrial engineering
Particle swarm optimization method in multiobjective problems
Proceedings of the 2002 ACM symposium on Applied computing
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Expert Systems with Applications: An International Journal
A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Machine learning for dynamic multi-product supply chain formation
Expert Systems with Applications: An International Journal
An adaptive genetic algorithm with dominated genes for distributed scheduling problems
Expert Systems with Applications: An International Journal
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Hi-index | 12.05 |
This paper introduces the algorithm portfolio concept to solve a combinatorial optimization problem pertaining to a supply chain. The supply chain problem is modeled with capacity constraints and demand variations over different time periods to minimize the total supply chain configuration cost. The algorithm portfolio is implemented over various problem instances to inspect and alleviate the computational expensiveness of a solution strategy. A bunch of five algorithms are utilized hereby viz. AIS, GA, Endosymbiotic Optimization, PSO and Psychoclonal algorithm. The observations reflect the appropriateness and effect of algorithm portfolios over the adopted supply chain, and viability over other optimization problems.