Perishable products run their life cycle in a short period of time due to the shortness of their shelf lives. Product efficiency falls when especially non-recyclable products are thrown away without being used. Furthermore, this kind of products that unnecessarily occupy shelves of supermarkets cause supermarkets to follow an insufficient stock management policy. Unconscious and unplanned use of our limited natural resources will deteriorate the product portfolio for future generations. Such unconscious production and consumption patterns will disrupt natural balance and damage sustainability of products. In addition to creating very high costs for producers, sellers and consumers alike, these unsold or stale products lead to environmental problems due to such pricing policies. In other words, although the products have to be thrown away without being sold is attributed by many managers to be attributable to the unplanned over-orders, the actual reason is something else. The real contributor of the problem is changing purchase attitudes of customers because of wrong pricing policies of wholesaler. In addition, limited resources are also consumed fast and in unnecessary amounts. The imbalance in respect to the sustainability of these products leads to increase in the production costs, procurement costs and failure to achieve balance among products to be kept in storage houses as some of the products occupy stocks unnecessarily. In the present study, a new pricing policy is developed for product stock whose shelf lives are about to expire and generally become waste to increase salability of these products in reference to fresher stocks of these products. The present study, which is designed to reduce the above-mentioned losses, will seek to minimize the cost of waste, maximize the profit earned by supermarkets from the product, maximize product utilization rates and ensure sustainability of products and stocks as well. Fulfillment of these objectives will increase productivity and enhance the significance of product efficiency and nature-friendly attitudes.

No abstract

No abstract

In order to produce more efficient, sustainable-clean energy, accurate prediction of wind turbine design parameters provide to work the system efficiency at the maximum level. For this purpose, this paper appears with the aim of obtaining the optimum prediction of the turbine parameter efficiently. Firstly, the motivation to achieve an accurate wind turbine design is presented with the analysis of three different models based on artificial neural networks comparatively given for maximum energy production. It is followed by the implementation of wind turbine model and hybrid models developed by using both neural network and optimization models. In this study, the ANN-FA hybrid structure model is firstly used and also ANN coefficients are trained by FA to give a new approach in literature for wind turbine parameters’ estimation. The main contribution of this paper is that seven important wind turbine parameters are predicted. Aiming to fill the mentioned research gap, this paper outlines combined forecasting turbine design approaches and presents wind turbine performance in detail. Furthermore, the present study also points out the possible further research directions of combined techniques so as to help researchers in the field develop more effective wind turbine design according to geographical conditions.

No abstract