Production policy for damageable items with variable cost function in an imperfect production process via genetic algorithm

• Authors: M. K. Maiti;M. Maiti
• Venue: Mathematical and Computer Modelling: An International Journal
• Year: 2005

This paper gives an appropriate solution to the contradiction faced during the inventory of displayed damageable items where both demand and damageability are stock-dependent. In this model, more stock increases the demand and ultimately fetches more profit but at the same time, invites more damage bringing down the profit amount. Moreover, the classical inventory models normally assume the production process to be perfectly reliable with a fixed set-up cost. In practice, it is not so. In this paper, an inventory model for a damageable item is formulated following profit maximization principle. Here, the unit production cost depends on production rate and is derived from the particular production function under which it is being produced. Demand for the item is directly proportional to stock and inversely proportional to unit selling price. Also, the units are kept in heaped stock and hence, likely to be damaged due to it. Flexibility of the production process, which is not perfectly reliable, is introduced in the manufacturing system by the generalized cost function. The set-up cost, the reliability of the production process, production rate and the inventory amount are the decision variables. Due to highly nonlinearity of the average profit function (i.e., objective function), it is optimized using contractive mapping genetic algorithm (CMGA) for the global optimal solution. Numerical examples are presented to illustrate the model and some useful comments/decisions are derived for a decision maker (DM). Results are obtained via greedy search algorithm (GSA) and simulated annealing (SA) also and compared with those obtained from CMGA.