This paper formulates a two-echelon singleproducer multi-buyer supply chain model, while a single product is produced and transported to the buyers by the producer. The producer and the buyers apply vendormanaged inventory mode of operation. It is assumed that the producer applies economic production quantity policy, which implies a constant production rate at the producer. The operational parameters of each buyer are sales quantity, sales price and production rate. Channel profit of the supply chain and contract price between the producer and each buyer is determined based on the values of the operational parameters. Since the model belongs to nonlinear integer programs, we use a discrete particle swarm optimization algorithm (DPSO) to solve the addressed problem; however, the performance of the DPSO is compared utilizing two well-known heuristics, namely genetic algorithm and simulated annealing. A number of examples are provided to verify the model and assess the performance of the proposed heuristics. Experimental results indicate that DPSO outperforms the rival heuristics, with respect to some comparison metrics.
A discrete particle swarm optimization algorithm with local search for a production-based two-echelon single-vendor multiple-buyer supply chain
2015-05-04
oai:zenodo.org:3813543
Journal of Industrial Engineering International 12(1) 29-43
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Vendor-managed inventory , Economic production quantity , Supply chain , Particle swarm optimization , Closed-loop supply chain network design , Competitive location , Contract design , Facility disruptions , Fuzzy logic , Genetic Algorithm , Heuristic algorithm , Location-allocation problem , Lost sales , Maximal covering location problem , Multi-echelon , NSGA-II , Quota allocation , SCOR , Social responsibility , Supplier selection , Supply chain management , Sustainable supply chain network design , Tabu search , Vendor Managed Inventory
An integrated vendor–buyer model with stock-dependent demand
Elsevier | 2010
|An integrated vendor–buyer model with stock-dependent demand
Online Contents | 2010
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