An optimization model for a monopolistic firm serving an environmentally conscious market: Use of Chemical Reaction Optimization Algorithm

Choudhary, A.; Suman, R.; Dixit, V.; Tiwari, M.; Fernandes, K.; Chang, P.

Abstract

This work 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 emission 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. To address above trade-off, a Non-Linear Programming (NLP) model with a maximization quadratic profit function has been formulated. Recently developed, Chemical Reaction Optimization algorithm, with superior computational performance, has been adopted to solve the NLP. The output of the model provides near optimal monopolistic price, best attainable reduction in manufacturing emissions through proportional investment and makes 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 work provides a decision making tool to determine the near optimal degree of each of the above dimension in multiple business fronts.

Citation

Choudhary, A., Suman, R., Dixit, V., Tiwari, M., Fernandes, K., & Chang, P. (2015). An optimization model for a monopolistic firm serving an environmentally conscious market: Use of Chemical Reaction Optimization Algorithm. International Journal of Production Economics, 164, 409-420. https://doi.org/10.1016/j.ijpe.2014.10.011

• Journal Article Type: Article
• Acceptance Date: Aug 29, 2014
• Online Publication Date: Nov 4, 2014
• Publication Date: Jun 1, 2015
• Deposit Date: Oct 19, 2017
• Publicly Available Date: Oct 20, 2017
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Electronic ISSN: 1873-7579
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 164
• Pages: 409-420
• DOI: https://doi.org/10.1016/j.ijpe.2014.10.011
• Public URL: https://durham-repository.worktribe.com/output/1346122