Loading...

A parameter-tuned genetic algorithm to solve multi-product economic production quantity model with defective items, rework, and constrained space

Pasandideh, S. H. R ; Sharif University of Technology | 2010

882 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s00170-009-2432-x
  3. Publisher: 2010
  4. Abstract:
  5. The economic production quantity (EPQ) model is often used in manufacturing environments to assist firms in determining the optimal production lot size that minimizes the overall production-inventory costs. While there are some unrealistic assumptions in the EPQ model that limit its real-world applications, in this research, some of these assumptions such as (1) infinite availability of warehouse space, (2) all of the produced items being perfect, and (3) the existence of one product type are relaxed. In other words, we develop a multi-product EPQ model in which there are some imperfect items of different product types being produced such that reworks are allowed and that there is a warehouse space limitation. Under these conditions, we formulate the problem as a nonlinear integer-programming model and propose a genetic algorithm to solve it. At the end, a numerical example is presented to identify the optimal values of the genetic algorithm parameters and to illustrate the applications of the proposed methodology to more realistic real-world problems
  6. Keywords:
  7. Imperfect and scrap items ; Constrained space ; Defective items ; Economic production quantity ; Economic production quantity models ; EPQ models ; EPQ, multi-product ; Inventory costs ; Manufacturing environments ; Multi-products ; Numerical example ; Optimal production ; Optimal values ; Product types ; Programming models ; Real-world application ; Real-world problem ; Warehouse space ; Genetic algorithms ; Industrial economics ; Integer programming ; Optimization ; Warehouses ; Parameter estimation
  8. Source: International Journal of Advanced Manufacturing Technology ; Volume 49, Issue 5-8 , July , 2010 , Pages 827-837 ; 02683768 (ISSN)
  9. URL: http://link.springer.com/article/10.1007/s00170-009-2432-x