Multi-response optimization of charcoal briquettes process for green economy using a novel TOPSIS linear programming and genetic algorithms based on response surface methodology
Narathip Pawaree, Surasit Phokha, Chawisorn Phukapak
Abstract
The production of charcoal briquettes was based on the concept of utilizing waste for sustainable and eco-friendly solutions within the green economy. This study introduces a new approach for optimizing important properties of charcoal briquettes. The approach aims to determine the appropriate operating conditions using a hybrid method. It integrates a novel TOPSIS linear programming with genetic algorithms based on response surface methodology. The experiment used an optimal mixture ratio of 25:10:6, including coconut shell, bagasse ash, and corncob. The results of the responses showed increased heating value and burning time by 5.13 % and 5.71 %, respectively, and moisture content decreased by 15.12 %. Furthermore, confirmation experiments within a 95 % confidence interval verified that the three responses obtained at the optimal operating conditions of process factors. The total cost of charcoal briquettes is 0.903 USD/kg and a payback period of 4.85 years. This illustrates that process improvement also aligns with the broader goals of promoting green and a circular economy.