POLLUTION CONTROL MULTI-OBJECTIVE INVENTORY MODEL OF PRODUCT-PROCESS INNOVATION WITH STOCK DEPEND DEMAND AND GATHERING KNOWLEDGE ACCUMULATION IN FINITE TIME HORIZON
Santu Hati*, Dr. Kalipada Maity**
*Department of Mathematics, Mugberia Gangadhar Mahavidyalaya, West Bengal, India
**Department of Mathematics, Mugberia Gangadhar Mahavidyalaya, West Bengal, India
- ISBN: 978-1-387-65048-4
- DOI: 10.25215/1387734229.09
In recent years, Governments and policymakers have conferred the important attention to global warming. The accompanying improvement of industries, the emission of greenhouse gases such as carbon dye oxide, carbon monoxide, sulfur dye oxide etc. is one of the primary reasons of global warming. To control the pollution and climate change for protect our environment, policymaker want to put their best efforts. For this intention, we have discussed a multi-objective pollution control product-process innovation inventory model with learning by doing effect, where the first objective function is for economical profit with maximizing form and second objective function for calculating the quantity of the pollutant gases with minimizing form. In this study the demand of the product depends on quality, selling price and stock, where the stock and quality have positive effect to the demand but the selling price has negative effect to it. In addition the quality/cost of the product is increased/decreased with increase the gathering knowledge accumulation of product and process innovation. Finally, this optimal control problem solved by using Pontryagin Maximum principle and for numerical result and graphical representation we use Runge-Kutta forward-backward method of fourth order using MATLAB software. Subsequently, the numerical results are presented both in tabular form and graphically.