Abstract
This paper presents a production-inventory model for deteriorating items with stock-dependent demand under inflation in a random planning horizon. The supplier offers the retailer fully permissible delay in payment. It is assumed that the time horizon of the business period is random in nature and follows exponential distribution with a known mean. Here learning effect is also introduced for the production cost and setup cost. The model is formulated as profit maximization problem with respect to the retailer and solved with the help of genetic algorithm (GA) and PSO. Moreover, the convergence of two methods—GA and PSO—is studied against generation numbers and it is seen that GA converges rapidly than PSO. The optimum results from methods are compared both numerically and graphically. It is observed that the performance of GA is marginally better than PSO. We have provided some numerical examples and some sensitivity analyses to illustrate the model.
Highlights
In the present competitive market, the supplier influences the customers in many different ways to capture the market
This paper presents a production-inventory model for deteriorating items with stock-dependent demand under inflation in a random planning horizon
A realistic production-inventory model for deteriorating items has been considered under inflation and permissible delay in payments with stock-dependent demand, over a random planning horizon
Summary
In the present competitive market, the supplier influences the customers in many different ways to capture the market. Taking the above shortcomings into account, this paper presents some EPQ models for a deteriorating item considering delay in payment and linearly stock-dependent demand with a random planing horizon, that is, the life time of the product is assumed as random in nature and follows an exponential distribution with a known mean. We formulate a production-inventory model for deteriorating items under inflation over a random planning horizon incorporating learning effect using permissible delay period. À ETOCN À EIkPN: ð5Þ where ESRN, EIkEN, EPCN, EHCN, ETOCN, and EIkPN are present values of expected total sales revenue, expected total interest earned, expected total production cost, Fig. 2 a Pictorial representation for the inventory model for case 2(a). PSO can provide a more stable and reliable solution, because it yields significantly smaller standard deviation
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