International Journal of Operational Research · 2020 · 11 citations · 0 references
ManagementIndustrial EngineeringOperations ManagementInventory ControlInventory ManagementOptimizationCombinatorial OptimizationInteger ProgrammingInventory OptimizationLot SizingSupplier SelectionSupply Chain OptimizationGenetic Algorithm OptimizationInventory PlanningLead TimeLead Time ConstraintsMixed-integer Linear ProgrammingMixed-integer Lot Sizing ModelsMixed-integer ProgrammingMulti-item Lot Sizing
This study presents an application of genetic algorithm (GA) for solving the multi-item inventory lot-sizing problem with supplier selection under discounts and lead time constraints. A mixed-integer linear programming (MILP) model is developed for proposed problem. To solve the problem, a genetic algorithm (GA) with two additional operations is proposed for handling the effect of the problem size. An adaptor for adjusting a chromosome data before the evaluation process and a penalty step for deterring an infeasible solution are developed. Finally, numerical examples are generated to evaluate the performance of the proposed GA, and the comparison with MILP approach about the solution quality and time is presented.