Non Dominated Sorting Genetic Algorithm for Chance Constrained Supplier Selection Model with Volume Discounts [chapter]

Remica Aggarwal, Ainesh Bakshi
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
more » ... ic algorithm solution methodology can solve the problems quite efficiently in minimal computational time. The experiments demonstrated that the genetic algorithm and uncertain models could be a promising way to address problems in businesses where there is uncertainty such as the supplier selection problem.
doi:10.1007/978-3-319-05458-2_48 fatcat:7a74qa3cqvbtjfe2shpvt6cr5e