Optimization on Production‐Inventory Problem with Multistage and Varying Demand
Duan Gang,
Chen Li,
Li Yin-Zhen,
Song Jie-Yan and
Akhtar Tanweer
Journal of Applied Mathematics, 2012, vol. 2012, issue 1
Abstract:
This paper addresses production‐inventory problem for the manufacturer by explicitly taking into account multistage and varying demand. A nonlinear hybrid integer constrained optimization is modeled to minimize the total cost including setup cost and holding cost in the planning horizon. A genetic algorithm is developed for the problem. A series of computational experiments with different sizes is used to demonstrate the efficiency and universality of the genetic algorithm in terms of the running time and solution quality. At last the combination of crossover probability and mutation probability is tested for all problems and a law is found for large size.
Date: 2012
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1155/2012/648262
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2012:y:2012:i:1:n:648262
Access Statistics for this article
More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().