Dr. V. Durga Prasada Rao
Dr. V. Ramachandra Raju
Dr. K. Venkata Subbaiah
Prof. T. V. Subba Rao
Abstract
Multi-objective optimization in multi-item inventory problems means determination of the optimal quantities of inventories which optimize the desired objectives. In the present paper a multi item inventory problem, which has the difficulty of obtaining satisfactory estimates of relevant inventory costs, is solved by formulating it as a multi-objective optimization problem (MOOP). A multi objective evolutionary algorithm - Non-dominated sorting genetic algorithm (NSGA-II) is used to solve the MOOP. It gives a Pareto optimal front of multiple non-dominated solutions in a single simulation run. Tofind a best Pareto optimal pointfrom among the entire set, a modifiedform of compromise programming approach is used.
Keywords- Multi-item, multi-objective, inventory, Genetic Algorithm.