Multi-item EPQ model with learning effect on imperfect production over fuzzy-random planning horizon  

作　　者：Amalesh Kumar Manna Barun Das Jayanta Kumar Dey Shyamal Kumar Mondal 

机构地区：[1]Department of Applied Mathematics with Oceanology and Computer Programming,Vidyasagar University,Midnapore-721102,WB,India [2]Department of Mathematics,Sidho-Kanho-Birsha University,Purulia,WB,India [3]Department of Mathematics,Mahishadal Raj College,Mahishadal,721628,WB,India

出　　处：《Journal of Management Analytics》2017年第1期80-110,共31页管理分析学报（英文）

摘　　要：Uncertainty is certain in the world of uncertainty.This study revisits an economic production quantity(EPQ)model with shortages for stock-dependent demand of the items with reworking and disposing of the imperfect ones over a random planning horizon under the joint effect of inflation and time value of money,where the expected time length is imprecise in nature.Transmission of learning effect has been incorporated to reduce the defective production.The total expected profit over the random planning horizon is maximized subject to the imprecise space constraint.The possibility,necessity and credibility measures have been introduced to defuzzify the model.The simulation-based genetic algorithm is used to make decision for the above EPQ model in different measures of uncertainty.The model is illustrated through an example.Sensitivity analysis shows the impacts of different parameters on the objective function in the model.

关 键 词：imperfect production REWORK SHORTAGE learning effect random planning horizon genetic algorithm 

分 类 号：F42[经济管理—产业经济]