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Non Dominated Sorting Genetic Algorithm for Chance Constrained Supplier Selection Model with Volume Discounts
[chapter]
2014
Lecture Notes in Computer Science
This paper proposes a Stochastic Chance-Constrained Programming Model (SCCPM) for the supplier selection problem to select best suppliers offering incremental volume discounts in a conflicting multi-objective scenario and under the event of uncertainty. A Fast Non-dominated Sorting Genetic Algorithm (NSGA-II), a variant of GA, adept at solving Multi Objective Optimization, is used to obtain the Pareto optimal solution set for its deterministic equivalent. Our results show that the proposed
doi:10.1007/978-3-319-05458-2_48
fatcat:7a74qa3cqvbtjfe2shpvt6cr5e