OPTIMIZATION OF A PRODUCTION LOT SIZING PROBLEM WITH QUANTITY DISCOUNT

Dynamic lot sizing problem is one of the significant problem in industrial units and it has been considered by  many researchers. Considering the quantity discount in  purchasing cost is one of the important and practical assumptions in the field of inventory control models and it has been less focused in terms of stochastic version of dynamic lot sizing problem. In  this paper, stochastic dynamic lot sizing problem with considering the quantity discount is defined  and  formulated.  Since  the  considered  model  is  mixed  integer  non-linear programming,  a  piecewise  linear  approximation  is  also  presented.  In  order  to  solve  the mixed integer non-linear programming, a branch and bound algorithm are presented. Each node in the branch and bound algorithm is also MINLP which is solved based on dynamic programming framework. In each stage in this dynamic programming algorithm, there  is a sub-problem which can be solved with lagrangian relaxation method. The numeric results found in this  study indicate that the proposed algorithm solve the problem faster than the mathematical  solution  using  the  commercial  software  GAMS.  Moreover,  the  proposed algorithm for  the  two  discount  levels  are  also  compared  with  the  approximate  solution  in mentioned software. The results indicate that our algorithm up to 12 periods not only can reach to the exact solution, it consumes less time in contrast to the approximate model.