An optimization model for a monopolistic firm serving an environmentally conscious market: Use of chemical reaction optimization algorithm

This research considers a monopolist firm which faces the following twin challenges of serving an environmentally sensitive market. The first challenge is the demand’s elasticity to emissions and price. To entice its environmentally conscious customers and generate higher demand, the firm incrementally invests in cleaner production technologies. It also adopts a voluntary limit on its emissions from transportation. However, such investments and penalty lead to the second challenge of reduced net profit. In order to address these challenges and establish a trade-off, this research develops a Non-Linear Programming (NLP) model with a maximization quadratic profit function. Furthermore, a Chemical Reaction Optimization algorithm, with superior computational performance, has been applied to solve the developed NLP models. The output results of the model provide near optimal monopolistic price, best attainable reduction in manufacturing emissions through proportional investment and a choice of suitable mode of transportation for each type of product offered by the firm. Three types of sensitivity analyses were performed by varying contextual parameters: customers’ emission elasticity, penalty charged per unit emission and investment coefficient. The results underpin the importance of investments in cleaner technologies and the need of financial aids for profit maximizing firms operating in cleaner markets. This research provides a decision making model to determine the near optimal degree of each of the above dimensions in multiple business fronts.